This PDF file contains the front matter associated with SPIE Proceedings Volume 9469, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

Future large aperture space telescopes may use lightweight correctable active mirrors. The Naval Postgraduate School’s Segmented Mirror Telescope (SMT) test bed uses 1-meter silicon carbide (SiC) active mirror segments to form a sixsegment deployable 3-meter telescope. The active segments suffer from residual surface errors after a correction is applied. A deformable mirror is added at the SMT pupil plane to improve this residual error. The large active SMT segment represents the woofer, and a small continuous micro-electro-mechanical system (MEMS) deformable mirror represents the tweeter. A global influence matrix and closed loop constrained least squares controller command the active segment and additional deformable mirror as a single device. An interferometer measures the surface error and provides feedback to the controller. Simulation and experimental results demonstrate a significant improvement in wavefront error compared to a 2-step sequential woofer-tweeter constrained least squares control approach.

This research paper deals with methods for improving the performance of Electro-optical detection systems designed to find Resident Space Objects (RSOs). Some methods for detecting RSOs rely on accurate knowledge of the system Point Spread Function (PSF). The PSF is a function of the telescope optics, the atmosphere, and other factors including object intensity and noise present in the system. Due to the random photon arrival times, any observed data will contain Poisson noise. Assuming that other noise sources such as dark current and readout noise do not contribute significantly, the final source of intensity fluctuations in the data is the atmosphere. To quantify these fluctuations, an optical model of a telescope system is developed, and its PSF is simulated. In a long exposure image, the effects of the atmosphere are well characterized with the long exposure atmosphere Optical Transfer Function (OTF). In contrast, a short exposure image does not average the fluctuations as effectively. To model the atmosphere, random phase screens with Kolmogorov statistics are added to the optical model to observe PSF fluctuations in short exposure telescope data. The distribution of the peak intensity is analyzed for varying exposure times and atmospheric turbulence strengths. This distribution is combined with the Poisson random arrival times of photons to create a combined model for received data, which is then used to design a new detection algorithm. The performance of the new space object detection algorithm will be compared to a traditional algorithm using simulated telescope data.

High-resolution infrared detector is used extensively for military and civilian purposes. Military applications include target acquisition, surveillance, night vision, and tracking. Civilian applications include, among others, scientific observations. For our space systems, we want to use the products developed by SOFRADIR Company. Thus, we have developed a space electronic unit that is used to control the high-resolution SCORPIO-MW infrared detector, which has a format of 640×512 pixels with 15μm×15μm pixel pitch. The detector within microelectronics based on infrared mid-wave (MW) complementary metal oxide semiconductors (CMOS) uses a micro-cooler in order to keep its temperature around 100 K. The standard wavelength range (3 to 5μm) is adapted to the 2.2 to 4.3μm wavelength range thanks to adaptation of the optical interface of the detector and with an antireflection coating. With our electronic system, we can acquire 3 images per second. To increase the signal to noise ratio, we have the opportunity to make a summation of 15 frames per image. Through this article, we will describe the space electronic system that we have developed in order to achieve space observations (e.g. Atmospheric Chemistry Suite package for ExoMars Trace Gas Orbiter).

An astronaut’s helmet is an invariant, rigid image element that is well suited for identification and tracking using current machine vision technology. Future space exploration will benefit from the development of astronaut detection software for search and rescue missions based on EVA helmet identification. However, helmets are solid white, except for metal brackets to attach accessories such as supplementary lights. We compared the performance of a widely used machine vision pipeline on a standard-issue NASA helmet with and without affixed experimental feature-rich patterns. Performance on the patterned helmet was far more robust. We found that four different feature-rich patterns are sufficient to identify a helmet and determine orientation as it is rotated about the yaw, pitch, and roll axes. During helmet rotation the field of view changes to frames containing parts of two or more feature-rich patterns. We took reference images in these locations to fill in detection gaps. These multiple feature-rich patterns references added substantial benefit to detection, however, they generated the majority of the anomalous cases. In these few instances, our algorithm keys in on one feature-rich pattern of the multiple feature-rich pattern reference and makes an incorrect prediction of the location of the other feature-rich patterns. We describe and make recommendations on ways to mitigate anomalous cases in which detection of one or more feature-rich patterns fails. While the number of cases is only a small percentage of the tested helmet orientations, they illustrate important design considerations for future spacesuits. In addition to our four successful feature-rich patterns, we present unsuccessful patterns and discuss the cause of their poor performance from a machine vision perspective. Future helmets designed with these considerations will enable automated astronaut detection and thereby enhance mission operations and extraterrestrial search and rescue.

Recent Better Buying Power (BBP) initiative for improving DoD’s effectiveness in developing complex systems includes "Owning the Technical Baseline" (OTB). This paper presents an innovative approach for the development of a "Resilient Program" Technical Baseline Framework (PTBF). The framework provides a recipe for generating the "Resilient Program²" Technical Baseline (PTB) components using the Integrated Program Management (IPM) approach to integrate Key Program Elements (KPEs)³ with System Engineering (SE) process/tools, acquisition policy/process/tools, Cost and Schedule estimating tools, DOD Architecture Framework (DODAF) process/tools, Open System Architecture (OSA) process/tools, Risk Management process/tools, Critical Chain Program Management (CCPM) process, and Earned Value Management System (EVMS) process/tools. The proposed resilient framework includes a matrix that maps the required tools/processes to technical features of a comprehensive reference U.S. DOD "owned" technical baseline. Resilient PTBF employs a new Open System Approach (OSAP) combining existing OSA⁴ and NOA (Naval Open Architecture) frameworks, supplemented by additional proposed OA (Open Architecture) principles. The new OSAP being recommended to SMC (Space and Missiles Systems Center) presented in this paper is referred to as SMC-OSAP⁵. Resilient PTBF and SMC-OSAP conform to U.S. DOD Acquisition System (DAS), Joint Capabilities Integration and Development System (JCIDS), and DODAF processes. The paper also extends Ref. 21 on "Program Resiliency" concept by describing how the new OSAP can be used to align SMC acquisition management with DOD BBP 3.0 and SMC’s vison for resilient acquisition and sustainment efforts.

In this paper, an implemented defense system is demonstrated to carry out cyber security situation awareness. The developed system consists of distributed passive and active network sensors designed to effectively capture suspicious information associated with cyber threats, effective detection schemes to accurately distinguish attacks, and network actors to rapidly mitigate attacks. Based on the collected data from network sensors, image-based and signals-based detection schemes are implemented to detect attacks. To further mitigate attacks, deployed dynamic firewalls on hosts dynamically update detection information reported from the detection schemes and block attacks. The experimental results show the effectiveness of the proposed system. A future plan to design an effective defense system is also discussed based on system theory.

Network sensor-based defense (NSD) systems have been widely used to defend against cyber threats. Nonetheless, if the adversary finds ways to identify the location of monitor sensors, the effectiveness of NSD systems can be reduced. In this paper, we propose both temporal and spatial perturbation based defense mechanisms to secure NSD systems and make the monitor sensor invisible to the adversary. The temporal-perturbation based defense manipulates the timing information of published data so that the probability of successfully recognizing monitor sensors can be reduced. The spatial-perturbation based defense dynamically redeploys monitor sensors in the network so that the adversary cannot obtain the complete information to recognize all of the monitor sensors. We carried out experiments using real-world traffic traces to evaluate the effectiveness of our proposed defense mechanisms. Our data shows that our proposed defense mechanisms can reduce the attack accuracy of recognizing detection sensors.

Game theory is a useful method to model interactions between agents with conflicting interests. In this paper, we set up a Game Theoretic Model for Satellite Communications (SATCOM) to solve the interaction between the transmission pair (blue side) and the jammer (red side) to reach a Nash Equilibrium (NE). First, the IFT Game Application Model (iGAM) for SATCOM is formulated to improve the utility of the transmission pair while considering the interference from a jammer. Specifically, in our framework, the frame error rate performance of different modulation and coding schemes is used in the game theoretic solution. Next, the game theoretic analysis shows that the transmission pair can choose the optimal waveform and power given the received power from the jammer. We also describe how the jammer chooses the optimal power given the waveform and power allocation from the transmission pair. Finally, simulations are implemented for the iGAM and the simulation results show the effectiveness of the SATCOM power allocation, waveform selection scheme, and jamming mitigation.

Accurate prediction of satellite communications (SATCOM) data link loss is critical for SATCOM systems to effectively achieve required Quality of Service (QoS) and link availability. A major challenge is to account for various sources of uncertainties (such as atmospheric loss, rain loss, depolarization loss, pointing offset loss, etc.,) and their impacts on the aggregated link loss. This paper investigates the use of Bayesian Network (BN) for acquiring accurate SATCOM link loss estimation and link budget analysis over various modulation and coding schemes. Based on the proposed BN models, a SATCOM Bayesian Network Analysis toolbox has been developed to support link budget analysis and decision making for robust SATCOM applications.

Radio frequency (RF) wireless communication is reaching its capacity to support large data rate transmissions due to hardware constraints (e.g., silicon processes), software strategies (e.g., information theory), and consumer desire for timely large file exchanges (e.g., big data and mobile cloud computing). A high transmission rate performance must keep pace with the generated huge volumes of data for real-time processing. Integrated RF and optical wireless communications (RF/OWC) could be the next generation transmission technology to satisfy both the increased data rate exchange and the communications constraints. However, with the promising benefits of RF/OWC, challenges remain to fully develop hybrid RF with wireless optical communications such as uniform waveform design for information transmission and detection. In this paper, an orthogonal frequency division multiplexing (OFDM) transmission scheme, which widely employed in RF communications, is developed for optical communications. The traditional high peak-to-average power ratio (PAPR) in OFDM is reduced to improve system performance. The proposed multi-carrier waveform is evaluated with a frequency-selective fading channel. The results demonstrate that bit error rate (BER) performance of our proposed optical OFDM transmission technique outperforms the traditional OWC on-off keying (OOK) transmission scheme.

This paper describes innovative frameworks to develop RFI modeling and prediction models for (i) estimating the RFI characteristics, (ii) evaluating effectiveness of the existing Unified S-Band (USB) command waveforms employed by civil, commercial and military SATOPS ground stations, and (iii) predicting the impacts of RFI on USB command systems. The approach presented here will allow the communications designer to characterize both friendly and unfriendly RFI sources, and evaluate the impacts of RFI on civil, commercial and military USB SATOPS systems. In addition, the proposed frameworks allow the designer to estimate the optimum transmitted signal power to maintain a required USB SATOPS Quality-of-Service (QoS) in the presence of both friendly and unfriendly RFI sources.

This paper presents a time division multiple access (TDMA) multiple-input and multiple-output (MIMO) synthetic aperture radar (SAR) with a sliding range window for automated position-keeping, which can be applied in vessel tracking/escorting, offshore deepwater drillship equipment servicing, etc. A MIMO SAR sensor predefines a special part of the target (i.e., the drillship, ship, or submarine) as the measurement target and does not need special assistant devices/targets installed on the target vessel/platform, so its application is convenient. In the measurement process, the sensor scans the target with multiple ranging gates, forms images of multiple sections of the target, detects the predefined part/target in these images, and then obtains the range and angle of the predefined target for relative localization. Our MIMO SAR has 13 transmitting antennas and 8 receiving antennas. All transmitting antennas share a transmitter and all receiving antennas share a receiver using switches to reduce cost. The MIMO SAR radar has 44 effective SAR phase centers, and the azimuth angle resolution is θ_0.5/44 (finest, θ _0.5 is the antenna element’s 3dB beamwidth). The transmitter transmits a chirped linear frequency modulated continuous wave (LFMCW) signal, and the receiver only processes the signal limited in the beat frequency region defined by the distance from the measurement target to the sensor and the interested measurement target extension, which is determined by the receiver bandwidth. With the sliding range window, the sensor covers a large range, and in the covered range window, it provides high accuracy measurements.

Wide area motion imagery (WAMI) has been attracting an increased amount of research attention due to its large spatial and temporal coverage. An important application includes moving target analysis, where vehicle detection is often one of the first steps before advanced activity analysis. While there exist many vehicle detection algorithms, a thorough evaluation of them on WAMI data still remains a challenge mainly due to the lack of an appropriate benchmark data set. In this paper, we address a research need by presenting a new benchmark for wide area motion imagery vehicle detection data. The WAMI benchmark is based on the recently available Wright-Patterson Air Force Base (WPAFB09) dataset and the Temple Resolved Uncertainty Target History (TRUTH) associated target annotation. Trajectory annotations were provided in the original release of the WPAFB09 dataset, but detailed vehicle annotations were not available with the dataset. In addition, annotations of static vehicles, e.g., in parking lots, are also not identified in the original release. Addressing these issues, we re-annotated the whole dataset with detailed information for each vehicle, including not only a target’s location, but also its pose and size. The annotated WAMI data set should be useful to community for a common benchmark to compare WAMI detection, tracking, and identification methods.

This paper investigates the problem of using a large number of independent, identical sensors jointly for multi-object detection and estimation (MODE), namely massive sensor MODE. This is significantly different to the general target tracking using few sensors. The massive sensor data allows very accurate estimation in theory (but may instead go conversely in fact) but will also cause a heavy computational burden for the traditional filter-based tracker. Instead, we propose a clustering method to fuse massive sensor data in the same state space, which is shown to be able to filter clutter and to estimate states of the targets without the use of any traditional filter. This non-Bayesian solution as referred to massive sensor observation-only (O2) inference needs neither to assume the target/clutter model nor to know the system noises. Therefore it can handle challenging scenarios with few prior information and do so very fast computationally. Simulations with the use of massive homogeneous (independent identical distributed) sensors have demonstrated the validity and superiority of the proposed approach.

This paper presents work conducted in preparation for a suborbital test flight to test an inertial measurement unit’s (IMU’s) ability to serve as a position determination mechanism in a GPS-denied environment. Because the IMU could potentially be used at several points during flight, it is not guaranteed that a GPS fix can be used to reset the IMU after the stresses of launch. Due to this, the specific goal of this work is to characterize whether a rocket launch disrupts the IMU-based position knowledge to the extent that it is unusable. This paper discusses preparations for a sub-orbital launch mission to this end. It include a description of the hardware and software used. A discussion of the data logging mechanism and the onboard and post-flight processing which is required to compare the GPS fixes and IMU-generated positions is also presented. Finally, the utility of an IMU capable of maintaining position awareness during launch is discussed.

Game theoretical methods have been used for spectral awareness, space situational awareness (SSA), cyber situational awareness (CSA), and Intelligence, Surveillance, and Reconnaissance situation awareness (ISA). Each of these cases, awareness is supported by sensor estimation for assessment and the situation is determined from the actions of multiple players. Game theory assumes rational actors in a defined scenario; however, variations in social, cultural and behavioral factors include the dynamic nature of the context. In a dynamic data-driven application system (DDDAS), modeling must include both the measurements but also how models are used by different actors with different priorities. In this paper, we highlight the applications of game theory by reviewing the literature to determine the current state of the art and future needs. Future developments would include building towards knowledge awareness with information technology (e.g., data aggregation, access, indexing); multiscale analysis (e.g., space, time, and frequency), and software methods (e.g., architectures, cloud computing, protocols).

This paper develops and evaluates a pursuit-evasion (PE) game approach for elusive orbital maneuver and space object tracking. Unlike the PE games in the literature, where the assumption is that either both players have perfect knowledge of the opponents’ positions or use primitive sensing models, the proposed PE approach solves the realistic space situation awareness (SSA) problem with imperfect information, where the evaders will exploit the pursuers’ sensing and tracking models to confuse their opponents by maneuvering their orbits to increase the uncertainties, which the pursuers perform orbital maneuvers to minimize. In the game setup, each game player P (pursuer) and E (evader) has its own motion equations with a small continuous low-thrust. The magnitude of the low thrust is fixed and the direction can be controlled by the associated game player. The entropic uncertainty is used to generate the cost functions of game players. The Nash or mixed Nash equilibrium is composed of the directional controls of low-thrusts. Numerical simulations are emulated to demonstrate the performance. Simplified perturbations models (SGP4/SDP4) are exploited to calculate the ground truth of the satellite states (position and speed).

Space situational awareness (SSA) is critical to many space missions serving weather analysis, communications, and navigation. However, the number of sensors used in space situational awareness is limited which hinders collision avoidance prediction, debris assessment, and efficient routing. Hence, it is critical to use such sensor resources efficiently. In addition, it is desired to develop the SSA sensor management algorithm in a distributed manner. In this paper, a distributed sensor management approach using the negotiation game (NG-DSM) is proposed for the SSA. Specifically, the proposed negotiation game is played by each sensor and its neighboring sensors. The bargaining strategies are developed for each sensor based on negotiating for accurately tracking desired targets (e.g., satellite, debris, etc.) . The proposed NG-DSM method is tested in a scenario which includes eight space objects and three different sensor modalities which include a space based optical sensor, a ground radar, or a ground Electro-Optic sensor. The geometric relation between the sensor, the Sun, and the space object is also considered. The simulation results demonstrate the effectiveness of the proposed NG-DSM sensor management methods, which facilitates an application of multiple-sensor multiple-target tracking for space situational awareness.

From December 2009 thru 2011 the NASA Wide-Field Infrared Survey Explorer (WISE) gathered radiometrically exquisite measurements of debris in near Earth orbits, adding substantially to the current catalog of known debris. Assuming grey-body emissivity, the apparent size of debris objects may be inferred from that data. This report describes a general model for debris size distributed near the GEO belt. Linear and nonlinear regression models were fit to data from the WISE orbital debris catalog. Using those results we estimate the sensitivity of the instrument to detection of small debris objects near the GEO belt.

This paper presents an automatic RSO detection and tracking scheme operating at the optical sensor system level. The software presented is a pipeline for processing ground or space-based imagery built from several subalgorithms which processes raw or calibrated imagery, detects and discriminates non-star objects, and associates observations over time. An orbit determination routine uses an admissible region to start off an unscented particle filter. This preliminary orbit estimate allows prediction of the appearance of the object in the next frame. A matched filter uses this imagery to provide feedback to the initial detection and tracking process.

The National Radio Astronomy Observatory (NRAO) builds, operates, and maintains a suite of premier radio antennas, including the 100m aperture Green Bank Telescope, the largest fully-steerable antenna in the world. For more than five decades the NRAO has focused on astrophysics, providing researchers with the most advanced instruments possible: large apertures, extremely low-noise receivers, and signal processors with high frequency and time resolution. These instruments are adaptable to Space Situational Awareness (SSA) tasks such as radar detection of objects in near-Earth and cis-Lunar space, high accuracy orbit determination, object surveillance with passive methods, and uplink and downlink communications. We present the capabilities of antennas and infrastructure at the NRAO Green Bank Observatory in the context of SSA tasks, and discuss what additions and modifications would be necessary to achieve SSA goals while preserving existing radio astronomy performance. We also discuss how the Green Bank Observatory’s surrounding topography and location within the National Radio Quiet Zone will enhance SSA endeavors.

It is a known fact that the amount of data about space that is stored is getting larger on an everyday basis. However, the utilization of Big Data and related tools to perform ETL (Extract, Transform and Load) applications will soon be pervasive in the space sciences. We have entered in a crucial time where using Big Data can be the difference (for terrestrial applications) between organizations underperforming and outperforming their peers. The same is true for NASA and other space agencies, as well as for individual missions and the highly-competitive process of mission data analysis and publication. In most industries, conventional opponents and new candidates alike will influence data-driven approaches to revolutionize and capture the value of Big Data archives. The Open Space Box Model is poised to take the proverbial “giant leap”, as it provides autonomic data processing and communications for spacecraft. We can find economic value generated from such use of data processing in our earthly organizations in every sector, such as healthcare, retail. We also can easily find retailers, performing research on Big Data, by utilizing sensors driven embedded data in products within their stores and warehouses to determine how these products are actually used in the real world.

The Thermal Infrared Compact Imaging Spectrometer (TIRCIS) is a long wave infrared (LWIR, 8-14 microns) hyperspectral imager designed as the follow-on to the University of Hawaii’s SUCHI (Space Ultra Compact Hyperspectral Imager). SUCHI is a low-mass (<9kg), low-volume (10x12x40cm³) LWIR spectrometer designed as the primary payload on the University of Hawaii-built 'HiakaSat' microsatellite. SUCHI is based on a variable-gap Fabry Perot interferometer employed as a Fourier transform spectrometer with images collected by a commercial off-the-shelf microbolometer contained inside a 1-atm sealed vessel. The sensor has been fully integrated with the HiakaSat microsatellite and is awaiting launch in 2015. The TIRCIS instrument is based on the same principles but takes lessons learned from SUCHI and applies them to a new design with improvements in spatial resolution, spectral resolution and spectral responsivity. The TIRCIS instrument is based on an uncooled microbolometer array with custom detector coatings to enhance responsivity towards 7 microns. Like SUCHI, TIRCIS utilizes a variable-gap Fabry Perot interferometer to create the spectra, but three different interferometer wedges with varying slopes resulting in spectral resolution ranging from 44 cm^-1 to 6.5 cm^-1 will be tested to explore tradeoffs between spectral resolution and sensitivity. TIRCIS is designed to achieve 120 m spatial resolution, compared with 230 m for SUCHI, from a theoretical 500 km orbit. It will be used for ground and aircraft data collection but will undergo environmental testing to demonstrate its relevance to the space environment. TIRCIS has been fully designed and is entering fabrication, with an operational instrument to be delivered in October, 2015.