Law enforcement agencies play a key role in protecting the nation from and responding to terrorist attacks. The National Institute of Justice (NIJ) is the focal point for the research, development, test and evaluation of technology for law enforcement. NIJ and the Department of Homeland Security's Directorate of Science & Technology (DHS S&T) have related missions to support research and technology development for public safety. DHS S&T provides law enforcement agencies technology to respond to terrorist threats involving weapons of mass destruction, while NIJ focuses on technologies applicable across the spectrum of law enforcement needs. Investment in C3I technology offers perhaps the greatest potential benefit with respect to improving the ability to law enforcement agencies to respond to all types of crime including terrorist acts. Providing effective communications and information systems remains a key technology challenge, as does providing law enforcement responders accurate information that they can act on. Sensors and surveillance systems can play a key role in identifying terrorists and preventing or effectively responding to a terrorist attack.

The Institute for Security Technology Studies (ISTS) was founded at Dartmouth College in 2000 as a national center of security research and development. The Institute conducts interdisciplinary research and development projects addressing the challenges of cyber and homeland security, to protect the integrity of the Internet, computer networks, and other interdependent information infrastructures. ISTS also develops technology for providing the information and tools necessary to assist communities and first responders with the evolving, complex security landscape. ISTS is a member of and administers the Institute for Information Infrastructure Protection (I3P), a consortium of 24 leading academic institutions, non-profits and federal laboratories that brings industry, academia and government together to articulate and focus on problems that need to be solved to help ensure the nation's information infrastructure is safe, secure, and robust.

The National Memorial Institute for the Prevention of Terrorism (MIPT) in Oklahoma City is a living memorial to the victims, survivors, family members and rescue workers affected by the April 19, 1995 bombing of the Murrah Federal Building. The Institute conducts research into the development of technologies to counter biological, nuclear and chemical weapons of mass destruction and cyberterrorism, as well as research into the social and political causes and effects of terrorism. This paper describes MIPT funded research in areas of detection, decontamination, personal protective equipment, attack simulations, treatments, awareness, improved public communication during and after an incident, as well as lessons learned from terrorist incidents.

Civil infrastructures are normally one of the most expensive investments in a nation. To ensure the security of our homeland, the integrity of critical infrastructural systems must be assessed periodically. The assessment of the performance and reliability of the infrastructures can be carried out effectively and efficiently through the use of a network of smart sensors. The smart sensors will constantly interrogate the state of the structural health and detect any initiation or progression of damage in the infrastructures. Proper warnings can be issued prior to structural failure to prevent catastrophic loss of lives and properties. In addition, the infrastructural health monitoring system can request a comprehensive structural performance re-evaluation when the deterioration of the structure has threatened the integrity. This paper reviews the current state of the art on applying smart piezoelectric sensors in infrastructural health monitoring. Experimental results for using smart sensors to detect the damage on some typical infrastructural components are presented. With the goal of constructing an automated on-line structural health monitoring system to constantly assess the integrity of critical infrastructural systems, this paper illustrated the promise of using the smart piezoelectric sensors in homeland security.

The National Guard Bureau (NGB) and the Naval Research Lab (NRL) have developed a Digital Mapping System (DMS) Portal System that currently connects over 360 geospatial data servers. The DMS Portal System is located at http://ngbcdmaps.gtri.gatech.edu and is being used by nationwide law enforcement (approximately 5000 users/month) to generate geospatial mapping solutions to satisfy broad requirements with no licensing required. This paper will highlight the current functionality of the DMS Portal System to allow many types of geospatial information (such as weather, conventional maps, imagery, plume model dispersions, etc.) to appear in a common environment regardless of how the information is originally stored. The DMS Portal System has substantial potential usage in the homeland defense arena as well as with conventional DoD/government and private sector users. Future directions for this cutting-edge technology will be outlined.

This paper describes the design for a content-based approach to detecting insider misuse by an analyst producing reports in an environment supported by a document control system. The approach makes use of Hidden Markov Models to represent stages in the Evidence-Based Intelligence Analysis Process Model (EBIAPM). This approach is seen as a potential application for the Process Query System / Tracking and Fusion Engine (PQS/TRAFEN). Actions taken by the insider are viewed as processes that can be detected in PQS/TRAFEN. Text categorization of the content of analyst's queries, documents accessed, and work product are used to disambiguate multiple EBIAPM processes.

Emergency responders are the front line of defense against catastrophic terrorist attacks on US soil. Advanced systems and cutting-edge technologies can increase responders' capabilities, or make their resources go farther in time of crisis, but there is a disconnection of understanding between those who produce the systems and technologies, and those who need them at the local level. Local jurisdictions rarely have a budget to support or influence technology development and acquisition. The laboratories, agencies, universities, or industries that develop these emerging technologies are responding to requirements from different markets (usually larger) than individual local jurisdictions. Indeed, responders may not even know of new technology development, availability, or relevance to responders’ needs. Consequently, technology developers have limited insight into what technologies responders need. Local, and even state, budgets by themselves are not sufficiently large or coordinated to influence technology development towards the needs of responders, without the assistance of federal direction and funding. If federal direction and funding of technology is to produce and deliver useful capabilities for local responders, federal technology planners must understand the needs of responders, and develop technology plans to meet those needs. Project Responder's National Technology Plan for Emergency Response provides a foundation and building blocks for technology planning, to focus federal research and development investments toward improving the capabilities of state and local emergency responders.

Military personnel and first responders are in critical need of a sensitive technology for the rapid evaluation and diagnosis of exposure to adverse chemical agents. Ideally such a technology would be automated, easily portable, possess a high degree of sensitivity and specificity, and provide non-invasive assessment of health status. A potential method for meeting these requirements is via monitoring of ocular characteristics. Due to the interconnection between the eyes and the various physiological systems of the body, insults to the body may create a unique "thumbprint" upon the eyes based upon how these various physiological systems are differentially affected. In turn, these thumbprints (biomarkers) may be used to perform diagnostic evaluations of an individual’s health status. Based upon this principle, the Ocular Scanning Instrumentation (OSI) technology is being developed as an automated device for non-invasive monitoring of optically apparent characteristics and attributes of the eyes for in-the-field diagnosis of battlefield traumas, insults, and threat agent exposures. The current manuscript presents comparative data for two of the agents which we have evaluated, carbon monoxide and cyanide. The defined methods provide the required specificity and sensitivity needed for detecting exposures at time points which provide an ample therapeutic window for medical intervention.

SRICO has developed a revolutionary approach to physiological status monitoring using state-of-the-art optical chip technology. The company’s patent pending Photrode is a photonic electrode that uses unique optical voltage sensing technology to measure and monitor electrophysiological parameters. The optical-based monitoring system enables dry-contact measurements of EEG and ECG signals that require no surface preparation or conductive gel and non-contact measurements of ECG signals through the clothing. The Photrode applies high performance optical integrated circuit technology, that has been successfully implemented in military & commercial aerospace, missile, and communications applications for sensing and signal transmission. SRICO’s award winning Photrode represents a new paradigm for the measurement of biopotentials in a reliable, convenient, and non-intrusive manner. Photrode technology has significant applications on the battlefield for rapid triage to determine the brain dead from those with viable brain function. An ECG may be obtained over the clothing without any direct skin contact. Such applications would enable the combat medic to receive timely medical information and to make important decisions regarding identification, location, triage priority and treatment of casualties. Other applications for the Photrode include anesthesia awareness monitoring, sleep medicine, mobile medical monitoring for space flight, emergency patient care, functional magnetic resonance imaging, various biopotential signal acquisition (EMG, EOG), and routine neuro and cardio diagnostics.

With the attack on the United States and the subsequent war on terror and the wars in Afghanistan and Iraq a need has been exposed for the transition of technology to all of our defenders both combat forces on the foreign battlefield and domestic forces here at home. The establishment of the Department of Homeland Security has also provided a focus on inserting technology to dramatically improve the capability of airport security forces, law enforcement, and all first responder networks. The drastic increase in the use of Special Forces in combat has also required new advanced technology capabilities at a much faster rate of development than the standard military procurement system. Technology developers must address the questions of interoperability, cost, commercialization, of how these groups will use the technology delivered and the adoption criteria of users in the deployment environment. The successful transition to the field must address the formation of complex concepts of operations in the user's adoption criteria. Prototype transition for two systems, a pocket infrared camera and an acoustic/seismic detector, will be highlighted in their effect on the wars in Iraq and Afghanistan and in the heightening of homeland security.

Identification of an active Internet worm is a manual process where security analysts must observe and analyze unusual activity on multiple firewalls, intrusion-detection systems or hosts. A worm might not be positively identified until it already has spread to most of the Internet, eliminating many defensive options. In previous work, we developed an automated system that can identify active worms seconds or minutes after they first begin to spread, a necessary precursor to halting the spread of the worm rather than simply cleaning up afterward. The system collects ICMP Destination Unreachable messages from instrumented network routers, identifies those patterns of unreachable messages that indicate malicious scanning activity, and then searches for patterns of scanning activity that indicate a propagating worm. In this paper, we compare the performance of two different detection strategies, our previous threshold approach and a new line-fit approach, for different worm-propagation techniques, noise environments, and system parameters. These techniques work for worms that generate at least some of their target addresses through a random process, a feature of most recent worms. Although both being powerful methods for fast worm identification, the new line-fit approach proves to be significantly more noise resistant.

Many defense and security applications involve the detection of a dynamic process. A process model describes the state transitions of an object, which evolves in time according to specific know laws. Given a process model, the process detection problem is to identify the existence of such a process in large amount of observation data. While Hidden Markov Models (HMMs) are widely used to characterize dynamic processes, it's usually hard to estimate those state transition and emission probabilities precisely in practice, especially if we don't have sufficient training data. An inaccurate process model could lead to high false alarm and misdetection rates and the inference result could be misleading in the decision-making process. To this end, we propose nonparametric weak models derived from HMMs to characterize dynamic processes. A weak model doesn't need the strong requirement for probability specification as in HMMs. In this paper, we analyze the properties of such weak models and propose recursive algorithms to compute the hypotheses of the hidden state sequence and the size of the hypothesis set. Further we analyze how to control the size of the hypothesis set by increasing the number of sensors to tune the structure of the emission matrix.

Hidden Discrete Event Systems Models (HDESM) are discrete event dynamical system models whose underlying internal state spaces are not directly observable. Observations on such systems are artifacts of the hidden, internal states and are not deterministically or uniquely associated with the hidden states. The distribution of an observation of a HDESM is typically given by a probability distribution conditioned on the hidden state of the system. Classical linear systems, Hidden Markov Models (HMM) and certain types of Petri Net models are examples of HDESM's. A major challenge in working with this type of model is the estimation of an HDESM's hidden states based on a sequence of observations. In some cases, well-known algorithms can be used to solve this problem. In many cases of practical interest, however, the complexity of those algorithms is too high to be practical. New ideas and algorithms are therefore needed for effective solutions to the state estimation problem. In this paper we will investigate sub-classes of HDESM's whose structure would allow efficient state estimation algorithms to exist. Such structures could be related to the sparsity and/or equivalence class structure of transition dynamics within the underlying discrete event system. Efficient algorithms that compute approximate solutions will be investigated with the goal of understanding the trade-offs between computational efficiency and estimation accuracy. Ideas on how to implement such trade-offs also are proposed.

The publish/subscribe paradigm of Message Oriented Middleware provides a loosely coupled communication model between distributed applications. Traditional publish/subscribe middleware uses keywords to match advertisements and subscriptions and does not support deep semantic matching. To this end, we designed and implemented a Semantic Message Oriented Middleware system to provide such capabilities for semantic description and matching. We adopted the DARPA Agent Markup Language and Ontology Inference Layer, a formal knowledge representation language for expressing sophisticated classifications and enabling automated inference, as the topic description language in our middleware system. A simple description logic inference system was implemented to handle the matching process between the subscriptions of subscribers and the advertisements of publishers. Moreover our middleware system also has a security architecture to support secure communication and user privilege control.

User interfaces are important for process modeling and detection systems. This paper discusses the user interface design and implementation for the innovative Process Query System (PQS). Discussion focuses on the Hidden Markov Model (HMM) editor, model validation, process query types, and result visualization. A log likelihood indicator is used to evaluate and visualize the goodness of model-observation matching. A numerical method to measure the distinguishability between two HMMs is proposed and proved effective. The measurement is performed by estimating misdetection rate using the Monte Carlo simulation method. A visual HMM comparison tool using this method is implemented in the user interface.

In this paper, we investigate the link between the rate at which events are observed by a monitoring system and the ability of the system to effectively perform its tracking and surveillance tasks. In general, higher sampling rates provide better performance, but they also require more resources, both computationally and from the sensing infrastructure. We have used Hidden Markov Models to describe the dynamic processes to be monitored and (alpha,beta)-currency as a performance measure for the monitoring system. Our ultimate goal is to be able to determine the minimum sampling rate at which we can still fulfill the performance requirements of our system. Along with the theoretical work, we have performed simulation-based tests to examine the validity of our approach; we compare performance results obtained by simulation with the theoretical value obtained a priori from the scenario parameters and illustrate with a simple example a technique for estimating the required sampling rate to achieve a given level of performance.

The Adaptive Safety Analysis and Monitoring (ASAM) system is a hybrid model-based software tool for assisting intelligence analysts to identify terrorist threats, to predict possible evolution of the terrorist activities, and to suggest strategies for countering terrorism. The ASAM system provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict terrorist network states. In combination with counter-terrorist network models, it can also suggest feasible actions to inhibit potential terrorist threats. In this paper, we will introduce the architecture of the ASAM system, and discuss the hybrid modeling approach embedded in it, viz., Hidden Markov Models (HMMs) to detect and provide soft evidence on the states of terrorist network nodes based on partial and imperfect observations, and Bayesian networks (BNs) to integrate soft evidence from multiple HMMs. The functionality of the ASAM system is illustrated by way of application to the Indian Airlines Hijacking, as modeled from open sources.

The secure information retrieval technologies are critical for status identification, particularly in the battlefield for friend/enemy discrimination. The materials or devices used in these technologies should be hard to find, difficult to counterfeit and as simple as possible. Moreover, if the coding information is totally position-invariant, i.e. neither sequence nor pixel based, it will greatly simplify the retrieval system. We describe an information retrieval technology, which possesses the above-mentioned features. The information is encoded by using luminescent semiconductor nanocrystals (or quantum-dots, QDs) mixed with a transparent solution, namely info-ink. When an exciting light beam shines at the info-ink, its emitting spectral features, i.e., wavelength and intensity, provide the encoded information. The info-ink could be applied on any kind of surface, for examples, document cover, top area of helmet, and even a fingernail. It is actually a thin layer of paint and requires no power supply. The retrieval device consists of an exciting light source, a mini-spectrometer and a data processing unit. However, for battlefield applications, a major problem with fluorescence-based technology is that the brightness of sunlight can overwhelm most reflected fluorescent signal. To overcome the shortcomings, the quantum dots are engineered to fluoresce at wavelengths corresponding to the absorption lines of the solar spectrum, more commonly known as Fraunhofer lines.

This paper will evaluate the feasibility of constructing a system to support intelligence analysts engaged in counter-terrorism. It will discuss the use of emerging techniques to evaluate a large-scale threat data repository (or Infosphere) and comparing analyst developed models to identify and discover potential threat-related activity with a uncertainty metric used to evaluate the threat. This system will also employ the use of psychological (or intent) modeling to incorporate combatant (i.e. terrorist) beliefs and intent. The paper will explore the feasibility of constructing a hetero-hierarchical (a hierarchy of more than one kind or type characterized by loose connection/feedback among elements of the hierarchy) agent based framework or "family of agents" to support "evidence retrieval" defined as combing, or searching the threat data repository and returning information with an uncertainty metric. The counter-terrorism threat prediction architecture will be guided by a series of models, constructed to represent threat operational objectives, potential targets, or terrorist objectives. The approach would compare model representations against information retrieved by the agent family to isolate or identify patterns that match within reasonable measures of proximity. The central areas of discussion will be the construction of an agent framework to search the available threat related information repository, evaluation of results against models that will represent the cultural foundations, mindset, sociology and emotional drive of typical threat combatants (i.e. the mind and objectives of a terrorist), and the development of evaluation techniques to compare result sets with the models representing threat behavior and threat targets. The applicability of concepts surrounding Modeling Field Theory (MFT) will be discussed as the basis of this research into development of proximity measures between the models and result sets and to provide feedback in support of model adaptation (learning). The increasingly complex demands facing analysts evaluating activity threatening to the security of the United States make the family of agent-based data collection (fusion) a promising area. This paper will discuss a system to support the collection and evaluation of potential threat activity as well as an approach fro presentation of the information.

There have been numerous efforts to create comprehensive databases from multiple sources to monitor the dynamics of public health and most specifically to detect the potential threats of bioterrorism before widespread dissemination. But there are not many evidences for the assertion that these systems are timely and dependable, or can reliably identify man made from natural incident. One must evaluate the value of so called 'syndromic surveillance systems' along with the costs involved in design, development, implementation and maintenance of such systems and the costs involved in investigation of the inevitable false alarms¹. In this article we will introduce a new perspective to the problem domain with a shift in paradigm from 'surveillance' toward 'awareness'. As we conceptualize a rather different approach to tackle the problem, we will introduce a different methodology in application of information science, computer science, cognitive science and human-computer interaction concepts in design and development of so called 'public health situation awareness systems'. We will share some of our design and implementation concepts for the prototype system that is under development in the Center for Biosecurity and Public Health Informatics Research, in the University of Texas Health Science Center at Houston. The system is based on a knowledgebase containing ontologies with different layers of abstraction, from multiple domains, that provide the context for information integration, knowledge discovery, interactive data mining, information visualization, information sharing and communications. The modular design of the knowledgebase and its knowledge representation formalism enables incremental evolution of the system from a partial system to a comprehensive knowledgebase of 'public health situation awareness' as it acquires new knowledge through interactions with domain experts or automatic discovery of new knowledge.

In this paper we present an effective steganalyis technique for digital video sequences based on the collusion attack. Steganalysis is the process of detecting with a high probability and low complexity the presence of covert data in multimedia. Existing algorithms for steganalysis target detecting covert information in still images. When applied directly to video sequences these approaches are suboptimal. In this paper, we present a method that overcomes this limitation by using redundant information present in the temporal domain to detect covert messages in the form of Gaussian watermarks. Our gains are achieved by exploiting the collusion attack that has recently been studied in the field of digital video watermarking, and more sophisticated pattern recognition tools. Applications of our scheme include cybersecurity and cyberforensics.

This paper presents an event sensing paradigm for intelligent event-analysis in a wireless, ad hoc, multi-camera, video surveillance system. In particilar, we present statistical methods that we have developed to support three aspects of event sensing: 1) energy-efficient, resource-conserving, and robust sensor data fusion and analysis, 2) intelligent event modeling and recognition, and 3) rapid deployment, dynamic configuration, and continuous operation of the camera networks. We outline our preliminary results, and discuss future directions that research might take.

Heretofore, we always thought of our greatest national security threats as being external. Now, however, the threat is pervasive, i.e., internal as well. As the attacks of September 11, 2001 exhibited, the old methods of collecting and analyzing information have failed to protect us from the terrorist threat. While new technologies exist to counter terrorism, there is a hesitation to accept many of these for fear that they intrude upon personal privacy. Hence, the Potomac Institute is seeking to create the policy paradigm that will allow for the use of new information technologies that will enable the disruption of terrorist before they occur, while protecting our fundamental civil liberties.

Explosives detection is a very important task for National Security. The formidable task includes development of new probes and methods for detection of concealed explosives which is of utmost priority to Homeland Security and other security enforcing federal agencies. Here we report on the detection of triacetone triperoxide (TATP) on metallic surfaces using a Fiber Optic Coupled FTIR method. FT-IR spectroscopy is well suited to be used outside the confinement of the sample compartment, provided the excitation source and the reflected light can be transported to the interferometer. Fiber optic cables that transmit in the Mid-IR range have made this possible by allowing the development of a range of spectroscopic probes for in situ analysis. In our study we used a specially designed sampling probe that operates at the grazing-angle to detect and to quantify μg/cm2 levels of explosives on stainless steel. Calibration curves were prepared using stainless steel plates, 3 inches wide x 6 inches long. The samples were deposited on the surface using a smearing method. To carry out the experiments, TATP was synthesized in the laboratory. For the calibration curves TATP was dissolved in dichloromethane. The standard solutions (20) μL were transferred on the plates resulting in surface mass concentrations of TATP that ranged from 8 to 150 μg/cm2. The data was analyzed using Chemometrics routines and Discriminant Analysis algorithms. In particular, multivariate Partial Least Squares (PLS) was used to determine the most significant peak for the analysis. In other experiments done with stainless steel plates coated with 150 μg/cm2 TATP, spectra were recorded every 27 seconds. For this concentration TATP sublimates to surface concentrations below detection in 800 s.

This study examines the sorption of explosives [TNT, RDX, PETN, TATP] to hair during exposure to their vapors. In each test, three colors of hair were simultaneously exposed to explosive vapor. Washing, extracting, and gas chromatographic quantification protocols were developed, and replication of quantitative data was confirmed. Results show that sorption of explosives, via vapor diffusion, to black hair is significantly greater than to blond, brown or bleached hair. Furthermore, the rate of sorption is directly related to the vapor density of the explosive: TATP >>> TNT >> PETN > RDX. Using TNT as the prototype, persistence of the explosive upon standing in air and upon repeated washing with sodium dodecyl sulfate was demonstrated. This study indicates that hair can be a useful indicator of explosive exposure/handling. Work is in progress to develop this technique into an effective forensic tool.

We report on the effect of trinitrotoluene (TNT) in the fluroescence emission of CdSe quantum dots covered with a ZnS core shell. Pulses of 100 femtoseconds are employed to excite the fluorescence of the dots off resonance. We found evidence for a strong quenching by TNT on the fluorescence emission of the quantum dots. The fluorescence emission of the QD experiences a blue or red shift that depends on the CdSe particle size and amount of TNT. The results are explained in terms of a charge transfer mechanism or a modification of the traps involved in electron relaxation in QD. The results show that QD are a promising tool for TNT sensing.

A method to screen for flammable and explosive materials in bottles by electromagnetic measurement is described. The technique makes use of an aluminum cavity having strong electromagnetic resonances in the radio wave band. An object inserted into the cavity changes the internal field configuration, and causes small, but measurable shifts in the resonant frequencies. The response depends on the electrical permittivity, or dielectric constant, of the material. By measuring the frequency change of many different cavity modes, the dielectric constant of the perturbing object can be inferred independently of the object's size and shape. We demonstrate the detection of materials in bottles using an experimental device.

Non nitrogen containing, organic peroxides explosives Triacetone triperoxide and diacetone diperoxide have been prepared in the laboratory in order to study various aspects of their synthesis and their experimental and theoretical spectroscopic characteristics. By using different proportions of acetone/hydrogen peroxide (Ac/H₂O₂), sulfuric, hydrochloric and methanosulfuric acids as catalyzers, it was possible to obtain both compounds in a rapid and simple form. Raman, IR spectroscopy, and GC-MS were used in order to determine the precursors, intermediates and final analytes. Experiments and theoretical studies using density functional theory (DFT) have been used in the elucidation step of the mechanism of the synthesis of the so called "transparent" explosives. The B3LYP functional with the 6-31G** basis set was used to carry out the electronic structure calculation of the intermediates and internal rotations and vibrations of TATP. Raman spectra of solid TATP and FTIR spectra of gas TATP, were recorded in order to assign the experimental spectra. Although full agreement with experiment was not obtained, spectral features of the main TATP bands were assigned.

Atomic force microscopy (AFM), scanning electron microscopy (SEM), white light imaging measurements, and Raman microscopy were employed for the characterization of RDX nanoparticles deposited on glass substrate surfaces. The RDX nanoparticles were prepared by exposure of glass substrate surfaces to an aerosol jet containing RDX. The spectroscopic signature of RDX particles and the two known forms of the material, β and α RDX, are compared. Raman measurements reveal that RDX nanoparticles and β deposits have similar spectroscopic signatures between 750 and 1000 cm^-1.

Object recognition and identification is one of essential parts for Homeland Security. There have been numerous researches dealing with object recognition using two-dimensional (2D) or three-dimensional (3D) imaging. In this paper, we address 3D object classification with computational holographic imaging. A 3D object can be reconstructed at different planes using a single hologram. We apply Principal Component Analysis (PCA) and Fisher Linear Discriminant (FLD) analysis based on Gabor-wavelet feature vectors to classify 3D objects measured by digital interferometry. The presented technique substantially reduces the dimensionality of the 3D classification problem. Experimental and simulation results are presented for regional filtering concentrated at specific positions, and for overall grid filtering.

A new type of fingerprint sensor is presented. The sensor maps the acoustic impedance of the fingerprint pattern by estimating the electrical impedance of its sensor elements. The sensor substrate, made of 1-3 piezo-ceramic, which is fabricated inexpensively at large scales, can provide a resolution up to 50 μm over an area of 20 x 25 mm2. Using FE modeling the paper presents the numerical validation of the basic principle. It evaluates an optimized pillar aspect ratio, estimates spatial resolution and the point spread function for a 100 μm and 50 μm pitch model. In addition, first fingerprints obtained with the prototype sensor are presented.

It is important to segment fingerprint image from background accurately, which could reduce time consumed on image preprocessing and improve the reliability of minutiae extraction. Methods for fingerprint image segmentation can be divided into two categories: at block level and at pixel level. This paper presents a method based on quadric surface model for fingerprint image segmentation, which belongs to method at pixel level. First, spatial distribution model of pixels based on Coherence, Mean and Variance is acquired and analyzed. 200 typical fingerprint images are selected from FVC2000 and FVC2002. The class of the pixel of these images, namely, fingerprint part or background part, is recorded manually. Coherence, Mean and Variance of each pixel are extracted and spatial distribution model of pixels is built by the use of different colors in displaying pixels of fingerprint part and pixels of background part. The model indicates that it is not linear apart and the performance of fingerprint image segmentation with a linear classifier is very limited. Second, a quadric surface formula is presented for fingerprint image segmentation and coefficients of the quadric surface formula are acquired by BP neural network. Last, in order to evaluate the performance of our method in comparison to a method using linear classifier, experiments are performed on FVC2000 DB2. Manual inspection shows that the proposed method provides accurate high-resolution segmentation results. Experimental result shows that only 0.97% of the pixels are misclassified by our method, and linear classifier misclassifies 6.8% of the pixels.

Face recognition has higher performance with controlled illumination and pose. But in some applications such as video surveillance, imaging condition is uncontrolled and the subject is not cooperative. In this paper pose invariant face recognition in complex backgrounds is discussed and a framework is proposed. Our algorithm is comprised of four parts. In the first part a face location algorithm combining face feature and template is proposed to determine the face location, represented as center of eyes and mouth. In the second part a face segmentation algorithm using curve fitting is proposed to segment face region in the image. The third part is face normalization---to obtain a front view face from a face with variant pose. In the forth part, the face recognition based on normalized faces is implemented using eigenface method. The algorithm is tested using 70 images of 14 persons, the experimental results confirm the efficiency of our algorithms.

For the boundary polygons of band-images, a fast constrained Delaunay triangulation algorithm is presented and based on it an efficient skeletonization algorithm is designed. In the process of triangulation the characters of uniform grid structure and the band-polygons are utilized to improve the speed of computing the third vertex for one edge within its local ranges when forming a Delaunay triangle. The final skeleton of the band-image is derived after reducing each triangle to local skeleton lines according to its topology. The algorithm with a simple data structure is easy to understand and implement. Moreover, it can deal with multiply connected polygons on the fly. Experiments show that there is a nearly linear dependence between triangulation time and size of band-polygons randomly generated. Correspondingly, the skeletonization algorithm is also an improvement over the previously known results in terms of time. Some practical examples are given in the paper.

Dogs have been used successfully to detect drugs and conventional high explosives. The world-wide rise in terrorist activities has placed emphasis on the detection of non-conventional explosive materials such as the multi-functional peroxides, triacetone triperoxide (TATP) and hexamethylene triperoxide diamine (HMTD). This study demonstrates that dogs can detect both solid TATP and TATP adsorbed to cotton balls. An effective procedure to train dogs to detect TATP using cotton balls permeated with TATP vapor is provided. The various trials showed that dogs were capable of detecting as little as 200 μg of TATP adsorbed to a one gram cotton ball under a variety of circumstances. However, since TATP vaporizes rapidly at room temperature, significant depletion of TATP from cotton balls can occur in as little as 20 minutes, hampering the ability of the dogs to detect it. The TATP depleted cotton ball can be refreshed by returning it to a sealed container with TATP residue for about 20 minutes. A presumed decomposition product of TATP, acetone, cannot be used in place of TATP to train dogs.

This paper proposed a new encryption method using Computer Generated Fourier Hologram in frequency domain. When the main frequency spectrum, i.e. brand and an encrypted information frequency spectrum are mixed, it will not recognized and copied. We will use the methods of Dot Matrix (Digital) Hologram Modulation and the filter to get real signal. One new multi-modulated dot matrix hologram is introduced. It is encoded using several gratings. These gratings have different angles of inclination and different periods in same dot, to enable us in obtaining more information.

Wireless Multimedia applications increasingly demand low power and bandwidth efficient techniques for content protection. Existing partial encryption methodologies juggle with the difficulties of trading decoding complexity for a higher bit rate, maintaining format compliance yet minimizing the number of components that need to be encrypted, to produce the desired distortion. Source based fingerprinting schemes for content tracking are neither bandwidth efficient nor computationally efficient when coupled with encryption. Thus inspired by the chameleon cipher we present a new algorithm for fingerprinting JPEG compressed images and a simple analytical model based on joint fingerprinting and decryption, as a computationally and bandwidth efficient solution for content protection and tracking.

Response and mitigation following a confirmed release of hazardous chemicals requires mapping of affected areas to determine evacuation and response procedures. In-situ sensors sample only locally while mapping requires remote sensors which can rapidly monitor large volumes from a distance. For use by first responders at all levels, sensors must be low-cost, simple, robust, battery operated, and relatively fast (< 1 s). A low-cost simple passive remote sensor based on multi-spectral infrared radiometry was demonstrated under laboratory conditions. The sensor consists of 8 uncooled pyroelectric infrared detectors with integrated bandpass filters selected to transmit radiation at bands that coincide with prominent spectral features of selected chemicals. Large radiative throughput achieved by detecting radiation through relatively broadband filters (20-30 cm^-1) permitted the use of low-cost, uncooled detectors without a significant loss of system sensitivity relative to high-specificity remote sensors, which require cryogenic cooling. A new modulation and radiation distribution technique was developed to provide well registered imaging by the detectors and the amplitude modulation that is necessary for detection with pyroelectric detectors. Results show that uncooled sensors can provide sufficient sensitivity to simulants of toxic chemicals (methanol, DMMP, and DIMP) with spectral features in the 8-12 micron region. In addition, the detector array provides signatures of the tested chemical simulants sufficient for identification.

A trailer based sensor system has been developed for remote chemical sensing applications. The sensor uses quantum cascade lasers (QCL) that operate in the long wave infrared. The QCL is operated continuous wave, and its wavelength is both ramped over a molecular absorption feature and frequency modulated. Lock-in techniques are used to recover weak laser return signals. Field experiments have monitored ambient water vapor and small quantities of nitrous oxide, tetrafluoroethane (R134a), and hydrogen sulfide released as atmospheric plumes. Round trip path lengths up to 10 km were obtained using a retroreflector. Atmospheric turbulence was found to be the dominating noise source. It causes intensity fluctuations in the received power, which can significantly degrade the sensor performance. Unique properties associated with QCLs enabled single beam normalization techniques to be implemented thus reducing the impact that turbulence has on experimental signal to noise. Weighted data averaging was additionally used to increase the signal to noise of data traces. Absorbance sensitivities as low as ~1x10^-4 could be achieved with 5 seconds of data averaging, even under high turbulence conditions.

Surface-enhanced Raman scattering (SERS) is emerging as a versatile and powerful technique for the detection of various defense related hazardous materials. This work illustrates the level of sensitivity and reproducibility achieved using SERS substrates with structural features engineered at the nanometer scale. Nanostructured substrates show significant sensitivity toward a number of different analytes. Pinacolyl methyl phosphonic acid (PMPA), a nerve-agent degradation product, was detected in less than 30 seconds at 1ppb. Para-nitroaniline, an explosives simulant, was detected in the same amount of time at 10 ppm. Multiple tests showed signal reproduction of PMPA at 100 ppb below a 7% standard deviation. The substrates are small and lightweight. In addition, a portable SERS spectrometer, equipped with a fiber coupling for excitation and detection, can act as the sensor body. On a previous occasion, electrochemically roughened SERS substrates were loaded into this portable spectrometer and deployed in the field for the successful blind detection of buried, defused, landmines. Such a system accommodates multiple substrate technologies, allowing sensing in the vapor and liquid phase as well as via solids extraction, and is compatible with nanoscale substrates.

Ion mobility spectrometry (IMS) is recognized as one of the most sensitive and robust techniques for the detection of narcotics, explosives and chemical warfare agents. IMS is widely used in forensic, military and security applications. Increasing threat of terrorist attacks, the proliferation of narcotics, Chemical Weapons Convention (CWC) treaty verification as well as humanitarian de-mining efforst have mandated that equal importance be placed on the time required to obtain results as well as the quality of the analytical data. In this regard IMS is virtually unrivaled when both speed of response and sensitivity have to be considered. The problem with conventional (signal averaging) IMS systems is the fixed duty cycle of the entrance gate that restricts to less than 1%, the number of available ions contributing to the measured signal. Furthermore, the signal averaging process incorporates scan-to-scan variations that degrade the spectral resolution contributing to misidentifications and false positives.

The dog's nose is an effective, highly-mobile sampling system, while the canine olfactory organs are an extremely sensitive detector. Having been trained to detect a wide variety of substances with exceptional results, canines are widely regarded as the 'gold standard' in chemical vapor detection. Historically, attempts to mimic the ability of dogs to detect vapors of explosives using electronic 'dogs noses' has proven difficult. However, recent advances in technology have resulted in development of detection (i.e., sampling and sensor) systems with performance that is rapidly approaching that of trained canines. The Nomadics Fido was the first sensor to demonstrate under field conditions the detection of landmines with performance approaching that of canines. More recently, comparative testing of Fido against canines has revealed that electronic vapor detection, when coupled with effective sampling methods, can produce results comparable to that of highly-trained canines. The results of these comparative tests will be presented, as will recent test results in which explosives hidden in cargo were detected using Fido with a high-volume sampling technique. Finally, the use of canines along with electronic sensors will be discussed as a means of improving the performance and expanding the capabilities of both methods.

We design and calibrate an efficient human detection system, capable of detecting and tracking a single person while minimizing the number of required sensors. Our infrared detectors have a 2 meter range and a 250ms rise/fall time. We sample their signal using an MSP430F149 microprocessor, correlate the results to reference patterns, and collect the binary decisions of each sensor on a workstation wirelessly. We modulate the optical field of the detectors by introducing selectively opaque reference structures into their optical path. Segmenting the physical space into signature cells enables direct measurement of source configuration. Brute force determination of the mapping is prohibitively expensive; we propose a method to estimate this mapping and predict signatures for every source position by observing signatures along prescribed tracks through the physical space.

This paper presents a design concept that can be used to monitor Micro-Electro-Mechanical Systems (MEMS) inertial sensors' random noise characteristics and dynamically track them for cancellation. The concept consists of a two-prong compensation approach offering both filtering and cancellation capability to effectively null out the MEMS sensor noise sources. The first path compensation will be fundamentally designed using high order filtering and calibration concept. This path is intended to effectively calibrate and remove high noise drift errors inherently existing in the MEMS sensors by using external aiding sensors data available on-board the spacecraft such as star tracker or GPS sensors. MEMS sensors' bias, scale factor, and misalignment stability errors will all be taken care of using this first prong design approach. The second compensation system will be designed using signal isolation and stochastic model propagation concept allowing on-line MEMS sensor's noise estimation and characterization. This second path is intended to dynamically monitor changes and identify MEMS inertial sensors' random noise parameters such as scale factor error, angular random walk, angular white noise, and rate random walk in a real-time fashion so that proper noise spectrum signatures can be obtained to update the process noise matrix of the calibration filter. This latter design approach can also be applied and implemented as a signal-conditioning device for MEMS sensors' internal self-calibration. The proposed algorithm is provided along with its preliminary results evaluated using simulation.

This paper presents a novel model and distributed algorithms for the cooperation and redeployment of mobile sensor networks. A mobile sensor network composes of a collection of wireless connected mobile robots equipped with a variety of sensors. In such a sensor network, each mobile node has sensing, computation, communication, and locomotion capabilities. The locomotion ability enhances the autonomous deployment of the system. The system can be rapidly deployed to hostile environment, inaccessible terrains or disaster relief operations. The mobile sensor network is essentially a cooperative multiple robot system. This paper first presents a peer-to-peer model to define the relationship between neighboring communicating robots. Delaunay Triangulation and Voronoi diagrams are used to define the geometrical relationship between sensor nodes. This distributed model allows formal analysis for the fusion of spatio-temporal sensory information of the network. Based on the distributed model, this paper discusses a fault tolerant algorithm for autonomous self-deployment of the mobile robots. The algorithm considers the environment constraints, the presence of obstacles and the nonholonomic constraints of the robots. The distributed algorithm enables the system to reconfigure itself such that the area covered by the system can be enlarged. Simulation results have shown the effectiveness of the distributed model and deployment algorithms.

This paper presents a fully automated and decentralized surveillance system for the problem of detecting and possibly tracking mobile unknown ground vehicles in a bounded area. The system consists ideally of unmanned aerial vehicles (UAVs) and unattended fixed sensors with limited communication and detection range that are deployed in the area of interest. Each component of the system (UAV and/or sensor) is completely autonomous and programmed to scan the area searching for targets and share its knowledge with other components within communication range. We assume that both UAVs and sensors have similar computing and sensing capabilities and differ only in their mobility (sensors are stationary while UAVs are mobile). Gathered information is reported to a base station (monitor) that computes an estimate of the global state of the system and quantifies the quality of the surveillance based on a measure of the uncertainty on the number and position of the targets overtime. The present solution has been achieved through a robotic implementation of a software simulation that was in turn realized under the principles of a novel top-down methodology for the design of provably performant agent-based control systems. In this paper we provide a description of our solution including the distributed algorithms that have been employed in the control of the UAV navigation and monitoring. Finally we show the results of an novel experimental performance analysis of our surveillance system.

Performance of seismic security systems relies on the particular application of the characteristics of seismic sensors. Current seismic sensors do not yield best possible results. In addition to identifying the requirements for optimal seismic sensors, we have developed seismic sensors for defense and security applications. We show two different types of seismic sensors: a miniscule, extremely low cost sensor and a bulk sensor. The miniscule, extremely low cost sensor is an electret-based geophone for both seismic and acoustic detection systems. This geophone detects a small size object - i.e. a walking/running/crawling person or a small underwater vehicle-that moves on the surface, underground, and/or in the water. It can also detect large size objects-i.e. heavy vehicles, trucks, tanks-as well as be used in littoral warfare. The electret-based design significantly improves technical characteristics achieving performance uniqueness: expanded frequency response range in the low frequency area, improved sensitivity threshold and accuracy response, and improved sensor's protection from electromagnetic interference. The bulk sensor has an extremely large detection surface, a nanocomposite body in special form casing, and a special electronic circuit. These sensors allow detection of footstep signals in high ambient seismic noise levels. However, installation requires significant installation groundwork effort.

In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

Cellular telephone antenna towers are evaluated as sites for rapid, effective & efficient deployment of counter-sniper sensors, especially in urban environments. They are expected to offer a suitable density, excellent LOS, and a generally limited variety of known or readily-characterized mechanical interfaces. Their precise locations are easily mapped in advance of deployment, are easily accessible by ground and air, and are easily spotted by deployment teams in real-time. We survey issues of EMI & RFI, susceptibility to denial & ambush in military scenarios, and the impact of trends in cell tower design & construction.

Planning Systems Incorporated (PSI) has been working with the National Institute of Justice, Center for Society Law and Justice (CSLJ) at the University of New Orleans, and law enforcement agencies in five highly varied United States locations over the past three years to evaluate the use of an automated, wireless acoustic gun fire detection and localization system. Considerable progress has been made in improving the sensor design, system engineering, software applications, deployment practices and manufacturing capabilities since last year's presentation. Two military variants have been developed as well. This paper will provide an updated status of SECURES technology and its utilization.

The Smart, White-Light Dazzler (SWLD) is a nonlethal weapon designed to aim and deliver a dazzling and disabling light flash of maximum eye-safe energy to a selected target. The two key features of the SWLD technology are its self-aiming and power-adjusting capabilities; optical barriers, such as dark glasses, rifle scopes, binoculars, etc., and iris aperture, whether the eyes are light or dark adapted, are automatically taken into account by using a low-power infrared (IR) laser to probe and return a glint from the eye(s) of the target. Using the retro-reflected glint the dazzle pulse is adjusted and directed to arrive at the target with maximum allowable nonlethal energy at any range from 1 m to 100 m. The collateral risk of this technology is very small. If the weapon is misaimed dramatically, the returned glint may come from an unintended person who will then be dazzled. Although this person will be incapacitated for 2-3 minutes, he will suffer no long-term effects. We assume all persons in dangerous situations would rather be accidentally, temporarily dazzled than suffer more serious consequences. The SWLD adds an important tool to the spectrum of nonlethal responses available for use by military and law enforcement personnel. Applications include dispersing persons in crowd control and disabling terrorists in hijacking situations. The dazzle process may be repeated, choosing the next most susceptible target until a crowd is subdued. One important application in counter-terrorism is onboard planes where a pilot can fire a SWLD through a cockpit-door window and dazzle a hijacker with no damage to passengers.

A modeling technique is presented that encapsulates the behavior of a crowd that may or may not become hostile. The various parameters such a slogans shouted, grouping, density, age, occasion, leadership, etc. among many other factors can easily be estimated and submitted to the model. The model will then begin a prediction process that can be corrected as more data is obtained. A predictor corrector process is described that re-guides the prediction process. In addition, we use the Metropolis simulation algorithm with input from the Boltzman weighting factor to determine how individuals within the crowd may be influenced to follow a particular path, and cellular automata to control the sphere of influence by one individual over another. Lastly, we provide some sample output from the model to illustrate the flow of such a dynamical environment.

Recent world events have identified needs for a commercial aircraft defense system against Man-Portable Air Defense Systems (MANPADS), such as SA-7 and Stinger shoulder launched surface-to-air missiles. Technical challenges include target detection, identification and countermeasures. Political and societal challenges include cost, time to deployment, ground and air safety, and reliability. These challenges, as well as many others, have been met and overcome with the development of Thor Systems' Commercial-Aircraft Protection System (C-APS). C-APS makes use of commercial technology such as radar and infrared sensors with a laser-based countermeasure. Unlike adapted military systems, C-APS detects the threat long before the military versions by employing a 360 degree hemispherical scan, identifying the threat with an infrared sensor and employing a directed laser to not only deflect the target but to permanently disable its seeker. Enhanced capabilities include multiple threat elimination and closed-loop technology for kill verification. All of this is accomplished with development costs less than half that required to convert military technology, manufacturing costs significantly less than competitive products, and a maintenance cycle coincident with standard FAA requirements, which are significantly longer than current systems.

A novel wireless local positioning system (WLPS) for airport (or indoor) security is introduced. This system is used by airport (indoor) security guards to locate all of, or a group of airport employees or passengers within the airport area. WLPS consists of two main parts: (1) a base station that is carried by security personnel; hence, introducing dynamic base station (DBS), and (2) a transponder (TRX) that is mounted on all people (including security personnel) present at the airport; thus, introducing them as active targets. In this paper, we (a) draw a futuristic view of the airport security systems, and the flow of information at the airports, (b) investigate the techniques of extending WLPS coverage area beyond the line-of-sight (LoS), and (c) study the performance of this system via standard transceivers, and direct sequence code division multiple access (DS-CDMA) systems with and without antenna arrays and conventional beamforming (BF).

That terrorists hijacked the airplanes and crashed the World Trade Center is disaster to civilization. To avoid the happening of hijack is critical to homeland security. To report the hijacking in time, limit the terrorist to operate the plane if happened and land the plane to the nearest airport could be an efficient way to avoid the misery. Image processing technique in human face recognition or identification could be used for this task. Before the plane take off, the face images of pilots are input into a face identification system installed in the airplane. The camera in front of pilot seat keeps taking the pilot face image during the flight and comparing it with pre-input pilot face images. If a different face is detected, a warning signal is sent to ground automatically. At the same time, the automatic cruise system is started or the plane is controlled by the ground. The terrorists will have no control over the plane. The plane will be landed to a nearest or appropriate airport under the control of the ground or cruise system. This technique could also be used in automobile industry as an image key to avoid car stealth.

A surveillance system that detects and tracks security breaches in airports is presented. The system consists of two subsystems with one overhead static and one Pan/Tilt/Zoom (PTZ) camera to first acquire and then follow an intruder who illegally walks into a crowded secure area of an airport. The overhead camera detects the intruder using a motion-based segmentation and an optical flow algorithm. Intruder handover from the overhead camera to the PTZ camera is then performed. A novel approach for intruder handover and feature extraction using color is presented for continuous tracking with the PTZ camera when the intruder moves out of the view of the overhead camera. We also use a mean shift filter with a newly designed non-rectangular search window which will be automatically updated to accurately localize the target. Real experimental results from a local airport are given and discussed.

It is well known to the Kalman filter design and estimation community that the values for the process noise, Q, and measurement noise, R, covariance matrices primarily dictate the filter performance. In addition, selecting proper values for Q and R is traditionally done in an ad-hoc manner. This paper provides a new look into the roles of the process noise and measurement noise matrices using the spacecraft attitude estimation problem as the design benchmark. This includes an interesting situation where the theoretical values of Q and R, derived as a function of gyro and star tracker noise parameters, are exactly matched with the noise characteristics employed on the sensor model side. However, the filter still exhibits poor attitude estimation performance, as measured against an attitude knowledge requirement, while subject to a high rate slew profile. A simulation based tuning methodology is developed to optimize the filter performance and bring the attitude estimation back to within the required attitude knowledge bound.

This paper examines the optimal placement of nodes for a Wireless Sensor Network (WSN) designed to monitor a critical facility in a hostile region. The sensors are dropped from an aircraft, and they must be connected (directly or via hops) to a High Energy Communication Node (HECN), which serves as a relay from the ground to a satellite or a high-altitude aircraft. The sensors are assumed to have fixed communication and sensing ranges. The facility is modeled as circular and served by two roads. This simple model is used to benchmark the performance of the optimizer (a Multi-Objective Genetic Algorithm, or MOGA) in creating WSN designs that provide clear assessments of movements in and out of the facility, while minimizing both the likelihood of sensors being discovered and the number of sensors to be dropped. The algorithm is also tested on two other scenarios; in the first one the WSN must detect movements in and out of a circular area, and in the second one it must cover uniformly a square region. The MOGA is shown again to perform well on those scenarios, which shows its flexibility and possible application to more complex mission scenarios with multiple and diverse targets of observation.

Seismic footstep detection-based systems are very important for various homeland security and military applications. Their performance and usefulness strongly depends on the characteristics of the seismic sensors. Unfortunately, currently available seismic sensors do not provide in satisfactory results. This paper describes the main issues of using seismic sensors for detection purposes and shows the key disadvantages of the most popular commercial seismic sensors/geophones. According to our results, the following are the key issues of poor seismic sensor performance: - Poor response to low frequency signals, leading to decrease of the detection range of targets - Unsatisfactory sensitivity threshold, causing missing low level seismic signals from outlying targets - Long damping signal time and corresponding low accuracy response, leading to problems with outlying target detection in high level noise environments - Low noise immunity from electromagnetic interference making seismic sensor operation in radar installation areas unreliable - Relatively bulky size and high price, which prevents extensive use of seismic sensors In addition, we have formulated objective requirements for seismic sensors to be used in defense and security applications

The current X-ray systems used by airport security personnel for the detection of contraband, and objects such as knives and guns that can impact the security of a flight, have limited effect because of the limited display quality of the X-ray images. Since the displayed images do not possess optimal contrast and sharpness, it is possible for the security personnel to miss potentially hazardous objects. This problem is also common to other disciplines such as medical X-rays, and can be mitigated, to a large extent, by the use of state-of-the-art image processing techniques to enhance the contrast and sharpness of the displayed image. The NASA Langley Research Center's Visual Information Processing Group has developed an image enhancement technology that has direct applications to the problem of inadequate display quality. Airport security X-ray imaging systems would benefit considerably by using this novel technology, making the task of the personnel who have to interpret the X-ray images considerably easier, faster, and more reliable. This improvement would translate into more accurate screening as well as minimizing the screening time delays to airline passengers. This technology, Retinex, has been optimized for consumer applications but has been applied to medical X-rays on a very preliminary basis. The resultant technology could be incorporated into a new breed of commercial x-ray imaging systems which would be transparent to the screener yet allow them to see subtle detail much more easily, reducing the amount of time needed for screening while greatly increasing the effectiveness of contraband detection and thus improving public safety.

With sponsorship from the National Institute of Justice and the Air Force Research Laboratory, AKELA developed a brassboard imaging radar suitable for portable, fixed in place operation with a maximum range of 100 meters. Experiments demonstrated that the radar detects an individual at a range of 12 meters through three internal walls, at 40 meters through dense foliage, and forms images through reinforced concrete walls. We found, however, that to be operationally practical, it would be necessary to increase the speed of the radar and display processing, and to develop a more robust imaging antenna array. A second generation radar imaging system is currently under development. The radar is frequency agile operating between 500 MHz and 2 GHz, has a maximum range of 250 meters, forms images at 10 frames per second, and uses a random array of antennas to improve image resolution and reduce ghosts.

This paper studies the capability of ultra-wideband short-pulse (UWB SP) radar to provide surveillance through concrete walls, including multistatic radar surveillance and 3D through-wall imaging. A full-wave electromagnetic simulator is used to generate high fidelity through-wall radar data. The raw radar data are transformed into radar images using a back projection algorithm. It is shown that UWB SP radar can track targets moving inside a room with concrete walls as well as providing static mapping of the room interior. The velocity of the electromagnetic wave inside a concrete wall is reduced compared to free space thus defocusing target images, displacing targets from their true positions, and possibly producing false targets. This problem can be mitigated by including the time of flight difference due to the concrete walls into the image generation algorithm. 3D through-wall radar imaging obtained using UWB SP radar centered at 2 GHz requires a very large antenna aperture to be able to see the shape of the human phantoms. However, using a center frequency of 10 GHz reduces this aperture requirement fivefold making the system more practical operationally. However, attenuation is much higher at 10 GHz than at 2 GHz.

We present the results of modeling intended to evaluate the feasibility of using neutrons from induced fission in highly enriched uranium (HEU) as a means of detecting clandestine HEU, even when it is embedded in absorbing surroundings, such as commercial cargo. We characterized radiation from induced fission in HEU, which consisted of delayed neutrons at all energies and prompt neutrons at energies above a threshold. We found that for the candidate detector and for the conditions we considered, a distinctive HEU signature should be detectable, given sufficient detector size, and should be robust over a range of cargo content. In the modeled scenario, an intense neutron source was used to induce fissions in a spherical shell of HEU. To absorb, scatter, and moderate the neutrons, we place one layer of simulated cargo between the source and target and an identical layer between the target and detector. The resulting neutrons and gamma rays are resolved in both time and energy to reveal the portion arising from fission. We predicted the dominant reaction rates within calcium fluoride and liquid organic scintillators. Finally, we assessed the relative effectiveness of two common neutron source energies.

Initial experiments have shown that plastic explosives and plastic material hidden on the body can be detected with a microwave noise radar system. This paper considers the basic physics of the technique and reports on the development of an initial prototype system for hand search of suspects and addresses the work carried out on optimising the Probability of Detection (PD) and False Alarm Rate (FAR).

Western democracies can reasonably expect an increase in homicide bombings as a major terrorist weapon of choice causing fear and economic damage far in excess of the actual loss of life and property caused by the explosives. The terrorists will strike at public venues (transportation, shopping, sporting events, schools, and governmental facilities) greatly multiplying the complexity and cost of effective defense. The author argues for accelerated research in multiple electromagnetic and passive technologies and fielding single and multi-sensor fixed, mobile and manportable systems to attempt to stay one step ahead of the growing reality of global terrorism.

An update to the performance of AS&E's Radioactive Threat Detection sensor technology. A model is presented detailing the components of the scintillant-based RTD system employed in AS&E products aimed at detecting radiological WMD. An overview of recent improvements in the sensors, electrical subsystems and software algorithms are presented. The resulting improvements in performance are described and sample results shown from existing systems. Advanced and future capabilities are described with an assessment of their feasibility and their application to Homeland Defense.

American Science and Engineering, Inc. has recently deployed X-ray inspection systems capable of screening large numbers of vehicles as they drive through a checkpoint. A general description of each of these transmission and backscatter X-ray inspection systems is presented. Other key integrated technologies are also described that enable screening of cargo using high quality X-ray images while the target vehicles are driven through the portal. Safety issues are discussed, as well as sample images created by fielded systems.

To increase the security and throughput of ISO traffic through international terminals more technology must be applied to the problem. A transnational central archive of inspection records is discussed that can be accessed by national agencies as ISO containers approach their borders. The intent is to improve the throughput and security of the cargo inspection process. A review of currently available digital media archiving technologies is presented and their possible application to the tracking of international ISO container shipments. Specific image formats employed by current x-ray inspection systems are discussed. Sample x-ray data from systems in use today are shown that could be entered into such a system. Data from other inspection technologies are shown to be easily integrated, as well as the creation of database records suitable for interfacing with other computer systems. Overall system performance requirements are discussed in terms of security, response time and capacity. Suggestions for pilot projects based on existing border inspection processes are made also.

There are approximately 261,000 rail crossings in the United States according to the studies by the National Highway Traffic Safety Administration (NHTSA) and Federal Railroad Administration (FRA). From 1993 to 1998, there were over 25,000 highway-rail crossing incidents involving motor vehicles - averaging 4,167 incidents a year. In this paper, we present a real-time computer vision system for the monitoring of the movement of pedestrians, bikers, animals and vehicles at railroad intersections. The video is processed for the detection of uncharacteristic events, triggering an immediate warning system. In order to recognize the events, the system first performs robust object detection and tracking. Next, a classification algorithm is used to determine whether the detected object is a pedestrian, biker, group or a vehicle, allowing inferences on whether the behavior of the object is characteristic or not. Due to the ubiquity of low cost, low power, and high quality video cameras, increased computing power and memory capacity, the proposed approach provides a cost effective and scalable solution to this important problem. Furthermore, the system has the potential to significantly decrease the number of accidents and therefore the resulting deaths and injuries that occur at railroad crossings. We have field tested our system at two sites, a rail-highway grade crossing, and a trestle located in Central Florida, and we present results on six hours of collected data.

Radar systems, which can operate in a variety of frequency bands, could provide significant flexibility in the operation of future Battle-space Management and Air Defense Systems (BMADS). Phased array antennas, which support high pulse rates and power, are well suited for surveillance, tracking and identifying the targets. These phased array antennas with the multiplicity of elements in phased array could provide accurate beam pointing, very rapid changes in beam location, and multiple beams, including algorithms for null steering for unwanted signals. No single radar band possesses characteristics that provide optimum performance. For example, L and S-bands are typically considered the best frequency ranges for acquisition and X-band is best for tracking. For many of the current phased array antennas the circuit components are narrow-band and therefore are not suitable for multi-band radar design. In addition, the cost, size, power dissipation, the weight, and, in general, the complexity has limited the development of multi-band phased array antenna systems. The system bandwidth of antenna array employing high loss phase shifters for beam steering also becomes limited due to the dispersion loss from the beam steering. As a result phased array radar design can result in a very large, complex, expensive, narrow band and less efficient system. This paper describes an alternative design approach in the design of wide-band phased array radar system based on multi-octave band antenna elements; and wide-band low loss phase shifters, switching circuits and T/R modules.

US Customs is responsible for monitoring all incoming air and maritime traffic, including the island of Puerto Rico as a US territory. Puerto Rico offers potentially obscure points of entry to drug smugglers. This environment sets forth a formula for an illegal drug trade - based relatively near the continental US. The US Customs Caribbean Air and Marine Operations Center (CAMOC), located in Puntas Salinas, has the charter to monitor maritime and Air Traffic Control (ATC) radars. The CAMOC monitors ATC radars and advises the Air and Marine Branch of US Customs of suspicious air activity. In turn, the US Coast Guard and/or US Customs will launch air and sea assets as necessary. The addition of a coastal radar and camera system provides US Customs a maritime monitoring capability for the northwestern end of Puerto Rico (Figure 1). Command and Control of the radar and camera is executed at the CAMOC, located 75 miles away. The Maritime Microwave Surveillance Radar performs search, primary target acquisition and target tracking while the Midwave Infrared (MWIR) camera performs target identification. This wide area surveillance, using a combination of radar and MWIR camera, offers the CAMOC a cost and manpower effective approach to monitor, track and identify maritime targets.

The authors report on recent progress of on-going research at Arizona State University for tracking aerosol plumes using remote sensing and modeling approaches. ASU participated in a large field experiment, Joint Urban 2003, focused on urban and suburban flows and dispersion phenomena which took place in Oklahoma City during summer 2003. A variety of instruments were deployed, including two Doppler-lidars. ASU deployed one lidar and the Army Research deployed the other. Close communication and collaboration has produced datasets which will be available for dual Doppler analysis. The lidars were situated in a way to provide insight into dynamical flow structures caused by the urban core. Complementary scanning by the two lidars during the July 4 firework display in Oklahoma City demonstrated that smoke plumes could be tracked through the atmosphere above the urban area. Horizontal advection and dispersion of the smoke plumes were tracked on two horizontal planes by the ASU lidar and in two vertical planes with a similar lidar operated by the Army Research Laboratory. A number of plume dispersion modeling systems are being used at ASU for the modeling of plumes in catastrophic release scenarios. Progress using feature tracking techniques and data fusion approaches is presented for utilizing single and dual radial velocity fields from coherent Doppler lidar to improve dispersion modeling. The possibility of producing sensor/computational tools for civil and military defense applications appears worth further investigation. An experiment attempting to characterize bioaerosol plumes (using both lidar and in situ biological measurements) associated with the application of biosolids on agricultural fields is in progress at the time of writing.

Calabazas Creek Research, Inc. is funded by the National Aeronautics and Space Administration to develop advanced backward wave oscillators that incorporate energy recovery, air cooling and improved performance. An improved coupler transforms the generated RF power to a high-purity, Gaussian output mode. The construction of a 600-700 GHz BWO is currently underway with higher frequency sources in development. Simulations predict 6-8 mW of RF power over a 100 GHz bandwidth.

This paper summarises the results of a 6 month deployment of a HF Surface Wave Radar (HFSWR) to demonstrate the detection and tracking of Go-Fast Boats (GFBs). Measured Doppler and Track data is compared to theoretical predictions. It is shown that HFSWR is a viable sensor for tracking GFBs in a target rich environment. Data is presented that demonstrates that detection ranges of 80 km can be achieved, providing vastly extended coverage far in excess of the line-of-sight limitations of conventional microwave radar.

The tremendous demand for Homeland Defense and Homeland Security (HD/HS) equipment for all types of commercial, industrial, civic, government and military facilities has resulted in an explosion of new applications for pan and tilt positioners. This paper discusses the technology of high performance positioning equipment in conjunction with various sensor systems now being utilized for HD/HS applications, and how this equipment is becoming more critical to the success of the HD/HS mission.

Every agent (combat unit) must plan and execute its own combat action series according to the instructions given by higher authority and its actual situation. Every combat action has a time interval, in order to guarantee the action's coordination within an agent or among some agents, every agent should analyze and compute the temporal relations between the actions that will be executed by its executors. Because there exist possible logical restricts and spacial, temporal or resource's conflicts between the actions, it's very important to correctly recognize temporal dependent relations between the actions, represent the preconditions of an action and design its executing action series for completion of combat mission. We discuss and analyze various dependent relations and put forward using Interval Algebra network and relation matrices to represent and compute the temporal relations.

In the military multi-agent system every agent needs to analyze the dependent and temporal relations among the tasks or combat behaviors for working-out its plans and getting the correct behavior sequences, it could guarantee good coordination, avoid unexpected damnification and guard against bungling the change of winning a battle due to the possible incorrect scheduling and conflicts. In this paper IA and PA network based computation of coordinating combat behaviors is put forward, and emphasize particularly on using 5x5 matrix to represent and compute the temporal binary relation (between two interval-events, two point-events or between one interval-event and one point-event), this matrix method makes the coordination computing convenience than before.

In order to enhance operational planning capabilities of the NATO Force Headquarters (KFOR, SFOR, ISAF), the NC3A Geo Team has developed a web-based interim geospatial intelligence support tool (IGEOSIT). The NC3A IGEOSIT displays geospatial data, such as digital topographic maps and satellite/air photo imagery, together with selectable overlay objects retrieved from distributed operational databases (DBs), for example minefields, bridges, culverts and military units. The NC3A IGEOSIT is a state-of-the-art web-based and Java-based multi-tier solution consisting of applications distributed over multiple servers within each Force HQ. The IGEOSIT provides advanced GIS terrain analysis capabilities based on the available Geo-data, including line-of-sight, 3-D perspective views, terrain profiles, and the definition of go/no-go areas. The system also performs vector-based route analysis and enhances the real-time tracking capabilities of mobile vehicles and troops. The IGEOSIT analyzes overlay data sets according to their attributes and dependencies in order to highlight otherwise hidden spatial relations that may be critical for mission planning. After performing geospatial analysis, the system compiles maps automatically to provide the user with immediate hard copy results, according to NATO standards, if necessary. The successful implementation of the IGEOSIT currently provides all NATO FORCE HQ staff members with a common operational picture of the theatre. This ensures that a common set of recently-updated information overlays forms the basis for all operational decisions. This paper describes the architecture, technology, performance tests (including test environment, analysis and measurement tools, hardware, selected test scenarios and results) and the lessons learned implementing advanced network and Java-based multi-tier solutions within the NATO Force Headquarters.

Architecture design of C4ISR system is the foundation for system integration. Based on C4ISR architecture framework, this paper analyzed the characters of architecture products, classified the design tools of architecture into different kinds and defined functions of design tools, proposed the architecture design integrate framework, and then realized architecture design tools and integrated environment.

The future requires military operations and intelligence communities to more heavily rely on Internet-based solutions for the delivery of MetOc data and products to the warfighter in an automated manner. These issues are being addressed by Tactical Environmental Data Services (TEDServices). TEDServices is being engineered by the Naval Research Laboratory, the Naval Oceanographic Office and the Naval Undersea Warfare Center, with sponsorship from Space and Naval Warfare Systems Command (SPAWAR) PMW-150. TEDServices was successfully demonstrated during April 2004, in FBE-Kilo, and is in transition to the US Navy this fiscal year. This paper will describe how TEDServices has been engineered to provide solutions to issues routinely confronted by warfighters. These solutions include, but are not limited to, better bandwidth usage, automated data ordering, simplification of data management, automated data transformations, forward deployed data caching, simplified integration with legacy tactical decision aids and support for joint interoperability.

Coherent homodyne detection using local laser oscillator is an important technique for applications requiring high receiver sensitivity. Conventional homodyne detection uses a continuous-wave (CW) local laser oscillator (LO) in which the only adjustable parameter is its average power. A pulsed LO with repetition rate same as the data symbol rate is proposed which provides new degree of freedom in receiver design, namely, its pulse shape and duty cycle. It is shown that pulsed LO is overall effective in enhancing receiver sensitivity compared with CW LO. We have investigated and compared the performance of coherent detection of 12.5 Gb/s binary phase-shift-keyed signals using integrated LiNbO₃ optical 90° hybrid with pulsed and CW LO for different receiver bandwidths. Our results showed that pulsed LO provide at least 2 dB in sensitivity improvement. We also observed that pulsed LO is effective in reshaping broadened signal pulses. Our simulation results agreed well with experiment and predicted that for a given signal and receiver bandwidth there is an optimal LO pulse width that gives maximum eye opening. Our simulation results also showed that pulsed LO is potentially effective in reducing penalty of pulse smearing as a result of beam steering impairment in free-space laser communications.

In this paper we present results from our research into the use of microgel-based photonic crystals in an optical tagging application. The basis for this research is the phenomena of self-assembly of hydrogel nano- and microparticles (i.e., microgels) into colloidal crystal Bragg reflectors. Previous research has demonstrated the assembly of Bragg structures that are sensitive in the visible spectral region. This current research focuses on the extension of this process into the infrared regime and the use of these infrared-sensitive structures in the creation of an optical tag. In particular, the research effort emphasizes two primary areas: the development of nanoparticles that are infrared-sensitive and the casting of thin films comprised of these particles. We will also present theoretical data on the optical and physical characteristics of thin films comprised of these particles. This paper will present an overview of the program, outline the processes and issues addressed during our initial efforts in creating these infrared sensitive structures and present a summary of the computational results based on the theoretical analyses.

2-D Optical Phased Array (OPA) antenna based on a Liquid Crystal On Silicon (LCoS) device can be considered for use in free space optical communication as an active beam controlling device. Several examples of the functionality of the device include: beam steering in horizontal and elevation direction; high resolution wavefront compensation in large telescope; beam shaping with computer generated kinoform. Various issues related to the diffraction efficiency, steering range, steering accuracy as well as magnitude of wavefront compensation is discussed.

This report documents the results of an internal DRS effort to develop an Ethernet based integrated defense system to improve defense of cities, harbors, airports, power production, energy supplies, bridges, monuments, dams and so forth. Results of the integration of multiple SCOUT LPI radars and multiple Electro-optical targeting systems will be provided, illustrating the benefits of interfacing surveillance radars with imaging sensors to confirm detection and provide visual recognition and identification. An analysis of the handover errors will be provided including errors due to; sensor platforms location and orientation uncertainty, target location measurement errors, data latency and motion prediction errors, which contribute to target handoff and the re-acquisition timeline. These predictions will be compared to measured results. The system architecture will be defined including; security, support for both stationary and moving sensor platforms, remote control of sensor systems and distribution of imagery through the network and remote diagnostics, maintenance and software upgrades. Growth capabilities include secure wireless communication to/from moving platforms, integration with sonar and seismic sensors, cooperative location of friendly forces and acoustic detection and triangulation of gunshots with automated cueing of sensors and security forces to the shooters most probable location. The use of ad hoc multi-hopping wireless networking supplements hardwire networks, augments disaster response capabilities, provides high-speed communications for moving platforms and supplements GPS outage areas.

This paper describes the inherent advantages of IR uncooled imagers in general, and the SCC500 in particular, for homeland defense. The SCC500 is a small, lightweight, low power, high performance uncooled imager that began production shipments in the spring of 2003. Key technologies described are dynamic range control, contrast enhancement and electronic zoom. Availability of these advanced features in production products are also described.

Uncooled thermal imaging was first introduced to the public in early 1980's by Raytheon (legacy Texas Instruments Defense Segment Electronics Group) as a solution for military applications. Since the introduction of this technology, Raytheon has remained the leader in this market as well as introduced commercial versions of thermal imaging products specifically designed for security, law enforcement, fire fighting, automotive and industrial uses. Today, low cost thermal imaging for commercial use in security applications is a reality. Organizations of all types have begun to understand the advantages of using thermal imaging as a means to solve common surveillance problems where other popular technologies fall short. Thermal imaging has proven to be a successful solution for common security needs such as: · vision at night where lighting is undesired and 24x7 surveillance is needed · surveillance over waterways, lakes and ports where water and lighting options are impractical · surveillance through challenging weather conditions where other technologies will be challenged by atmospheric particulates · low maintenance requirements due to remote or difficult locations · low cost over life of product Thermal imaging is now a common addition to the integrated security package. Companies are relying on thermal imaging for specific applications where no other technology can perform.

A low cost 16x16 un-cooled pyroelectric detector array, allied with advanced tracking and detection algorithms, has enabled the development of a universal detector with a wide range of applications in people monitoring and homeland security. Violation of access control systems, whether controlled by proximity card, biometrics, swipe card or similar, may occur by 'tailgating' or 'piggybacking' where an 'approved' entrant with a valid entry card is accompanied by a closely spaced 'non-approved' entrant. The violation may be under duress, where the accompanying person is attempting to enter a secure facility by force or threat. Alternatively, the violation may be benign where staff members collude either through habit or lassitude, either with each other or with third parties, without considering the security consequences. Examples of the latter could include schools, hospitals or maternity homes. The 16x16 pyroelectric array is integrated into a detector or imaging system which incorporates data processing, target extraction and decision making algorithms. The algorithms apply interpolation to the array output, allowing a higher level of resolution than might otherwise be expected from such a low resolution array. The pyroelectric detection principle means that the detection will work in variable light conditions and even in complete darkness, if required. The algorithms can monitor the shape, form, temperature and number of persons in the scene and utilise this information to determine whether a violation has occurred or not. As people are seen as 'hot blobs' and are not individually recognisable, civil liberties are not infringed in the detection process. The output from the detector is a simple alarm signal which may act as input to the access control system as an alert or to trigger CCTV image display and storage. The applications for a tailgate detector can be demonstrated across many medium security applications where there are no physical means to prevent this type of security breach.

Although the potential benefits of infrared imaging systems in law enforcement applications have been apparent for many years, budget and technology constraints have prevented their widespread deployment. Recent technology improvements and cost reductions, however, have made the routine use of handheld thermal imagers practical for the law enforcement community. This effort involved both an analysis of operational and technical requirements associated with law enforcement use as well as a comprehensive review of commercially available handheld infrared imaging systems. The use of handheld infrared systems in the counterdrug environment is also addressed, including the results of an analysis of proven applications, a review of training requirements, and a summary of legal issues associated with infrared surveillance. Results generated by the NVTHERM infrared sensor model are also shown for one handheld imager to provide representative information regarding low-cost thermal imager performance.

A 16x16 un-cooled thermal array based detector (ABD) offers the prospect of a new generation of security sensors, with high false alarm rejection and the ability to detect, track and count the number of intruders. The IRISYS array provides the ability not simply to detect an intruder, but by tracking them as a true moving target discriminate between real and false alarm sources. Target processing is carried out within the sensor allowing the position and size of each target within the field of view to be generated. The location and size for each target is output as a low bandwidth data message suitable for transmission over alarm signalling networks. A central security management system or alarm receiving centre display would provide an operator with an intruder count per room, a pseudo 'visual' display of targets and locations, show target vectors on a graphical display and track targets from room to room, allowing an appropriate response to be initiated. Taking the same concepts into external detection, should allow discrimination of humans versus animals or vermin and afford a high level of reasoning to reject environmentally generated false alarms. In external detection applications using the ABD as a trigger for CCTV, intruder location data would be used to steer and zoom a PTZ camera to achieve an identification view. As auto tracking features are added to the latest dome cameras the ABD's ability to track and output simultaneous data from multiple targets will steer a camera between several intruders.

We describe a new class of eye safe near infrared (~810 nm) illuminators based on diode laser sources. These illuminators are the most efficient available by a large margin. We show examples of how the high output allowed by lasers can be used to illuminate very large areas and improve images in difficult lighting situations. We also show examples of how the narrow specral band of laser light can be used with filtered cameras to achieve unique results in applications such as facial recognition in open daylight. Application data on effective ranges and other factors are presented. Comparisons are made with other lighting systems such as arc lamps, tungsten lamps and light emitting diodes. We also compare results of systems that operate without supplemental light such as intensified cameras and thermal infrared cameras.

Quantitative Structure-Property Relationships (QSPR) have been determined to predict retention times, explosives weight impact heights (H₅₀) and detonation velocities (DV). Electronic, geometric and topological descriptors were calculated through B3LYP/6-31G** method using Gaussian 03. Descriptors used were: the most positive charge (MPC), the energy of the lowest unoccupied molecular orbital (ELUMO) and the number of nitrogen atoms {N (N)}. A QSPR model was generated by multiple linear regression analysis using reported properties, as dependent variables. The reactivity of the compounds was also modeled. It was found that the reactivity can be drastically affected by the number of nitrogen atoms in the explosive. This QSPR approach offers a good explanation of the reactivity properties. For nitroaromatic explosives reactivities can be drastically affected by the electronic nature of the ring substituents and by their positions in the aromatic ring.

Process Query Systems (PQS) are a new kind of information retrieval technology in which user queries are expressed as process descriptions. The goal of a PQS is to detect the processes using a datastream or database of events that are correlated with the processes' states. This is in contrast with most traditional database query processing, information retrieval systems and web search engines in which user queries are typically formulated as Boolean expressions. In this paper, we outline the main features of Process Query Systems and the technical challenges that process detection entails. Furthermore, we describe several importance application areas that can benefit from PQS technology. Our working prototype of a PQS, called TRAFEN (for TRAcking and Fusion ENgine) is described as well.