Robert W. McMillan

Concealed weapon detection using microwave and millimeter wave sensors

Recent advances in millimeter-wave (MMW), microwave, and infrared (IR) technologies provide the means to detect concealed weapons remotely through clothing and in some cases through walls. Since the development of forward-looking infrared (FLIR) instruments, work has been ongoing in attempting to use these devices for concealed weapon detection based on temperature differences between metallic weapons and the background body temperature of the person carrying the weapon; however, the poor transmission properties of clothing in the infrared has led to the development of techniques based on lower frequencies. Focal plane arrays operating at MMW frequencies are becoming available which eliminate the need for a costly and slow mechanical scanner for generating images. These radiometric sensors also detect temperature differences between weapons and the human body background. Holographic imaging systems operating at both microwave and MMW frequencies have been developed which generate images of near photographic quality through clothing and through thin, non-metallic walls. Finally, a real-aperture radar is useful for observing people and detecting weapons through walls and in the field under reduced visibility conditions.

New law enforcement applications of millimeter-wave radar

Recent advances in millimeter-wave (MMW) radar technologies provide new applications for law enforcement use over-and- above the venerable speed timing radar. These applications include the potential to detect weapons under clothing and to conduct surveillance through walls. Concealed Weapon Detection and covert surveillance are of high interest to both the Department of Defense in support of Small Unit Operations and the Justice Department for civilian law enforcement applications. MMW sensors are under development which should provide the needed capabilities including radiometric sensors at 95 GHz, active 95 GHz real aperture radars, active focal plane array (FPA) radars, and holographic radars. Radiometric sensors include 2D FPA systems, 1D FPA, scanned systems, and single element scanned sensors. Active FPA radars include illuminated radiometric systems and coherent radar systems. Real aperture MMW radar systems include raster scanned and conical scanned sensors. Holographic systems ruse mechanical scanners to collect coherent data over a significant solid angular sector.

Sensors for military special operations and law enforcement applications

Improvement in the capabilities of infrared, millimeter- wave, acoustic, and x-ray, sensors has provided means to detect weapons concealed beneath clothing and to provide wide-area surveillance capability in darkness and poor light for military special operations and law enforcement application. In this paper we provide an update on this technology, which we have discussed in previous papers on this subject. We present new data showing simultaneously obtained infrared and millimeter-wave images which are especially relevant because a fusion of these two sensors has been proposed as the best solution to the problem of concealed weapon detection. We conclude that the use of these various sensors has the potential for solving this problem and that progress is being made toward this goal.

Imaging sensor fusion for concealed weapon detection

Sensors are needed for concealed weapon detection which perform better with regard to weapon classification, identification, probability of detection and false alarm rate than the magnetic sensors commonly used in airports. We have concluded that no single sensor will meet the requirements for a reliable concealed weapon detector and thus that sensor fusion is required to optimize detection probability and false alarm rate by combining sensor outputs in a synergistic fashion. This paper describes microwave, millimeter wave, far infrared, infrared, x-ray, acoustic, and magnetic sensors which have some promise in the field of concealed weapon detection. The strengths and weaknesses of these devices are discussed, and examples of the outputs of most of them are given. Various approaches to fusion of these sensors are also described, from simple cuing of one sensor by another to improvement of image quality by using multiple systems. It is further concluded that none of the sensors described herein will ever replace entirely the airport metal detector, but that many of them meet needs imposed by applications requiring a higher detection probability and lower false alarm rate.

ARPA/NIJ/Rome Laboratory concealed weapon detection program: an overview

Recent advances in passive and active imaging and non- imaging sensor technology offer the potential to detect weapons that are concealed beneath a persons clothing. Sensors that are discussed in this paper are characterized as either non-imaging or imaging. Non-imaging sensors include wide band radar and portal devices such as metal detectors. In general the strength of non-imaging sensors rest with the fact that they are generally inexpensive and can rapidly perform bulk separation between regions where persons are likely to be carrying concealed weapons and those regions that are likely to contain persons who are unarmed. The bulk process is typically accomplished at the expense of false alarm rate. Millimeter-wave (MMW), microwave, x-ray, acoustic, magnetic, and infrared (IR) imaging sensor technologies provide with greater certainty the means to isolate persons within a crowd that are carrying concealed weapons and to identify the weapon type. The increased certainty associated with imaging sensors is accomplished at the expense of cost and bulk surveillance of the crowd. CWD technologies have a variety of military and civilian applications. This technology focus area addresses specific military needs under the Defense Advanced Research Projects Agencys (DARPA) operations other than war/law enforcement (OOTW/LE). Additionally, this technology has numerous civilian law enforcement applications that are being investigated under the National Institute of Justices (NIJ) Concealed Weapons Detection program. This paper discusses the wide variety of sensors that might be employed in support of a typical scenario, the strengths and weaknesses of each of the sensors relative to the given scenario, and how CWD breadboards will be tested to determine the optimal CWD application. It rapidly becomes apparent that no single sensor will completely satisfy the CWD mission necessitating the fusion of two or more of these sensors.

A probabilistic model of the radar signal-to-clutter and noise ratio for Weibull-distributed clutter

We consider four effects relevant to the determination of the ratio of radar signal to clutter and noise. These effects are atmospheric turbulence, target fluctuations based on the Swerling models, zero-mean Gaussian background and receiver noise, and Weibull-distributed clutter. Radar return signal levels are affected by target fluctuations and atmospheric turbulence, characterized by target fluctuations according to the Swerling models and a lognormal distribution, respectively. Since these distributions are not independent and identically distributed (IID), they cannot be simply added, and must be treated by combining them in a manner similar to convolution. Also, clutter and noise are not IID, and must be combined in a similar way. The ratio of these two combinations comprises a probabilistic model of the ratio of radar signal to clutter and noise. This ratio is the probability that a given signal level will be achieved in the presence of atmospheric and target scintillations divided by the probability that a given clutter and noise level will be observed. To determine the ratio of the actual signal to clutter and noise, we must multiply these probabilities by the mean powers resulting from these phenomena, as will be shown later. We treat several cases of interest by varying the average radar cross section, the log intensity standard deviation of turbulence, the radar threshold-to-noise and signal-to-noise ratios, and the distribution of Weibull clutter mentioned above.

A model for determination of radome transmission, reflection, depolarization, loss, and effects on antenna patterns

Even though a radar antenna may be carefully designed to have low sidelobes and high radiation efficiency, a poorly designed radome can degrade its performance seriously. Degradation occurs both because of losses in the radome and by distortion in the antenna pattern as a result of deformation of the effective illumination pattern. In addition, radiation scattered from the radome may affect the radar performance by elevating antenna sidelobes, thus adding to the clutter that must be mitigated via signal processing. We present a method for analyzing radome performance and give examples of calculations showing transmission, reflection, loss, and antenna pattern effects for spherical and ogive radomes. The approach is sufficiently general for application to almost any radome shape.

A probabilistic model of the radar signal-to-clutter and noise ratio

We consider four effects relevant to the determination of the ratio of radar signal to clutter and noise. These effects are atmospheric turbulence, target fluctuations based on the Swerling models, zero-mean Gaussian background and receiver noise, and lognormal-distributed clutter. Radar return signal levels are affected by target fluctuations and atmospheric turbulence, characterized by a variant of the Rayleigh distribution and a lognormal distribution, respectively. Since these distributions are not independent and identically distributed (IID), they cannot be simply added, and must be treated by combining them in a manner similar to convolution. Also, clutter and noise are not IID, and must be combined in a similar way. The ratio of these two combinations comprises a probabilistic model of the ratio of radar signal to clutter and noise. This ratio is the probability that a given signal level will be achieved in the presence of atmospheric and target scintillations divided by the probability that a given clutter and noise level will be observed. To determine the ratio of the actual signal to clutter and noise, we must multiply these probabilities by the mean powers in these phenomena, as will be shown later. We treat several cases of interest by varying the average radar cross section, the log intensity standard deviation of turbulence, the radar threshold-to-noise and signal-to-noise ratios, and the distributions of lognormal clutter.

Survey of state-of-the-art technology in remote concealed weapon detection

Recent advances in millimeter-wave (MMV), microwave, and infrared (IR) technologies provide the means to detect concealed weapons remotely through clothing and is some cases through walls. Since the developemnt of forward-looking infrared instruments, work has been ongoing in attempting to use these devices for concealed weapon detection based on temperatrue differences between metallic weapons and in the infrared has led to the development of techniques based on lower frequencies. Focal plane arrays operating MMW frequencies are becoming available which eliminate the need for a costly and slow mechanical scanner for generating images. These radiometric sensors also detect temperature differences between weapons and the human body background. Holographic imaging systems operating at both microwave and MMW frequencies have been developed which generate images of near photographic quality through clothing and through thin, nonmetallic walls. Finally, a real- aperture radar is useful for observing people and detecting weapons through walls and in the field under reduced visibility conditions. This paper will review all of these technologies and give examples of images generated by each type of sensor. An assessment of the future of this technology with regard to law enforcement applications will also be given.

Electromagnetic detection in natural and man-made disasters

In a previous investigation [1–3] a theory for detecting complex objects embedded in complex dielectrics using the mathematical structure of the dyadic Greens function [4] was developed. The purpose of that study was to improve upon existing approximations for predicting the electromagnetic fields generated by and onto canonical structures such as loops and dipoles in conducting media. In this study, we develop a mathematical theory for detecting irregularly shaped structures in two region geometries that could be created by natural causes and man-made actions.