The field of autonomous vehicles is a rapidly growing one, with significant interest from both government and industry sectors. Autonomous vehicles represent the intersection of artificial
intelligence (AI) and robotics, combining decision-making with real-time control. Autonomous vehicles are desired for use in search and rescue, urban reconnaissance, mine detonation, supply convoys, and more. The general adage is to use robots for anything dull, dirty, dangerous or dumb. While a great deal of research has been done on autonomous systems, there are only a handful of fielded examples incorporating machine autonomy beyond the level of teleoperation, especially in outdoor/complex environments. In an attempt to assess and understand the current state of the art in autonomous vehicle development, a few areas where unsolved problems remain became clear. This paper outlines those areas and provides suggestions for the focus of science and technology research. The first step in evaluating the current state of autonomous vehicle development was to develop a definition of autonomy. A number of autonomy level classification systems were reviewed. The resulting working definitions and classification schemes used by the authors are summarized in the opening sections of the paper. The remainder of the report discusses current approaches and challenges in decision-making and real-time control for autonomous vehicles. Suggested research focus areas for near-, mid-, and long-term development are also presented.
Prompt gamma neutron activation analysis (PGNAA) has been proposed for confirming the presence of energetic materials as part of a mine or unexploded ordnance detection system. Ancore Corporation (previously SAIC Advanced Nucleonics Division), funded through Night Vision Electro Sciences Directorate by Environmental Security Test Certification Program, has carried out proof-of-concept demonstrations of PGNAA in this confirmatory role at Socorro, NM, and Yuma, AZ. In this, the first part of a two-part paper addressing the use of PGNAA in the detection of surface and near-surface UXO, we explore the phenomenology of PGNAA signals from surface or near-surface ordnance in soil to gain insight into the results of those demonstrations. PGNAA uses the high-energy gamma ray (10.8 MeV) from capture on N14 as a signature of the presence of nitrogen. This is one of the highest energy gamma rays resulting from neutron capture, and nitrogen is a major constituent of explosives, but a small portion of soil. Thus, PGNAA might be effective at confirming the presence of explosives. The phenomenology of dry soil is dominated by the two most common elements, oxygen and silicon. Neutrons injected into the soil elastically scatter from nuclei (predominantly oxygen), losing energy and propagating in a random walk fashion. Once slowed, neutron capture on soil elements produces a broad gamma-ray spectrum. Capture on Si29 produces a 10.6 MeV gamma, which is not resolvable from the nitrogen signal of interest using scintillation detectors. Thus, PGNAA will need either good resolution detectors, or robust background subtraction to estimate the silicon contribution. For any system unable to resolve the Si29 (10.6 MeV) and N14(10.8 MeV) gammas there is an inherently low signal to background, resulting primarily from the silicon in the soil. After background subtraction, there remains a challenging signal to noise level, where the noise is partly due to counting statistics and partly due to the modeling of the subtracted background.
We present an analysis of the use of thermal neutron analysis (TNA) to confirm the presence of energetic materials in unexploded ordnance detection. Our analysis is based on the performance of a prototype built by ANCORE and tested at Socorro, NM, and at Yuma, AZ, as part of the Environmental Security Technology Certification Program (ESTCP). From that data, we were able to develop a semi-empirical model for the expected signal strength as a function of the target's nitrogen content and depth. We found that the dependence on depth differs greatly between the two sites. We expect this simple model to be useful in future assessments of the feasibility of this approach. We also determine the Pd/PFA performance of the system at the two sites and found it to correspond to a signal-to-noise ratio of order unity. We estimate that an increase in signal-to-noise of roughly three will be necessary to extent the applicability of this technology in unexploded ordnance detection. Such improvements may be possible if the NaI detectors currently employed are replaced with high purity germanium (HPGe) detectors.
Mine and unexploded ordnance (UXO) detection systems must function in highly cluttered environments. Clutter leads to false alarms thereby hindering the detection and identification of targets of interest. Since the end user of the mine or UXO detection technology requires both a high detection rate and a low number of false alarms, technology demonstrations and system evaluations are designed to test these measures of performance. Detection rate and false- alarm rate are highly interdependent and must always be evaluated together. The relationship between the two rates directly affects the overall performance of the sensor in the field. Poor performance of a system in either detection rate or false-alarm rate causes a substantial increase in risk of undetected and thus unmarked or unremediated mines or UXO. A system with a low detection rate will leave many mines or UXO undetected. Performance can be traded between probability of detection and false-alarm rate by changing the system threshold. Raising or lowering the threshold will cause both the detections and false alarms to decrease or increase together. A system with a high false-alarm rate result in an increase in the time required to investigate potential targets. Therefore the rate of advance and rate of clearance decrease. With limited clearance resources, site coverage may become too time consuming or costly for operationally effective clearance, resulting in risk from undetected mines and UXO in areas that have not been searched. An assessment of the connection between detection rate nd false-alarm is presented. This relationship is discussed in the context of several government-sponsored in- field technology demonstrations of prototype and commercially available mine and UXO detection technologies, as well as real clearance operations. Implications of the results of these tests and the measures of performance are discussed in the context of real-world operations, including scenarios for clearance of miens in Bosnia and of UXO at DoD sites.
KEYWORDS: Target detection, Detection and tracking algorithms, Environmental sensing, Sensors, Signal to noise ratio, General packet radio service, Sensor performance, Magnetometers, Defense and security, Contamination
Between August 1993 and December 1994, the Army Environmental Center conducted a congressionally mandated demonstration of systems for the detection, identification, and remediation of unexploded ordance. Two sites were prepared at Jefferson Proving Ground with emplaced inert ordance of known type in recorded locations and orientations to provide ground truth against which demonstrator performance could be evaluated. Uncertainties due to the sensor, as well as surveying errors on the part of the demonstrators, make matching the demonstrator declarations with the emplaced items on a nontrivial exercise. At the same time, an accurate evaluation of system performance requires that this matching be done in a fair and objective fashion. The matching procedure uses a 'critical distance' to determine whether a demonstrator declaration matches an emplaced item and is, therefore, counted as a detection, or does not and is counted as a false alarm. Declarations that are within the critical distance from an emplaced item are candidates for matches, and those outside the critical distance are false alarms. As expected, the number of matches is a function of the choice of critical distance. Therefore, this distance was varied and the probability of detection was determined as a dependent variable in an attempt to separate true detections from random matches of false alarms to undetected baseline items. As a result of this and other tests, we have gained confidence that relative performance rankings are not dependent on an arbitrary choice of cut- off distance and that the evaluation procedure accurately reflects demonstrator performance at the Jefferson Proving Ground demonstration. In general, detection capabilites were lower than 65 percent and most demonstrators reported multiple false alarms per ordnance item detected.
Ultra-wideband radar (UWB) has been shown to be among the most powerful techniques available for underground and obscured object detection. The value of such systems is that they combine the penetration enhancement associated with VHF/UHF (and lower) frequencies with the resolution of wide absolute bandwidth. Such systems necessarily make use of much of the frequency spectrum already in heavy use by other services, such as television and mobile communications. Although this spectral overlap provides occasion for adverse consequences in both directions, to date the principal consequence has been often-severe impact on UWB radar measurements. Even in remote locations, the average interference power often exceeds receiver noise by many dB, becoming the limiting factor on system sensitivity. Nor are UWB radar designers free to overcome this interference by increasing radar power, since regulatory sanction for UWB operation will depend on maintaining sufficiently low spectral power densities to assure that other, prior, services are not appreciably degraded. Given the importance of radio frequency interference (RFI) on practical ultrawide band ground penetrating radar systems, it is important to consider how and to what extent the effects of RFI noise may be reduced. The overall problem of RFI and its impacts will be described and several signal processing approaches to removal of RFI will be discussed. These include spectral estimation and coherent subtraction algorithms and various filter approaches, which have been developed and applied by the signal processing community in other contexts. These methods will be applied to several different real-world experimental data sets, and quantitative measures of the effectiveness of each of these algorithms in removing RFI noise will be presented. Although computationally-intensive, most of the techniques to be described achieve substantial increases in S/RFI without requiring concomitant increases in radar average power.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.