The Close-In Detector (CID) is the vehicle-mounted multi-sensor anti-tank landmine detection technology for the Army CECOM Night Vision Electronic Sensors Directorate (NVESD) Mine Hunter-Killer (MH/K) Program. The CID includes two down-looking sensor arrays: a 20-antenna ground-penetrating radar (GPR) and a 16-coil metal detector (MD). These arrays span 3-meters in front of a high mobility, multipurpose wheeled vehicle (HMMWV). The CID also includes a roof-mounted, forward looking infrared (FLIR) camera that images a trapezoidal area of the road ahead of the vehicle. Signals from each of the three sensors are processed separately to detect and localize objects of interest. Features of candidate objects are integrated in a processor that uses them to discriminates between anti-tank (AT) mines and clutter and produces a list of suspected mine locations which are passed to the neutralization subsystem of MH/K. This paper reviews the current design and performance of the CID based on field test results on dirt and gravel mine test lanes. Improvements in CID performance for probability of detection, false alarm rate, target positional accuracy and system rate of advance over the past year and a half that meet most of the program goals are described. Sensor performances are compared, and the effectiveness of six different sensor fusion approaches are measured and compared.
This paper investigates the fusion of the confidence outputs of the Energy Based Processing (EBP) algorithm from the BAE Systems and the HMM GPR algorithm from the Univ. of Missouri to increase the performance of the Mine Hunter/Killer (MH/K) vehicle mounted landmine detection system. The EBP algorithm is based on the energy changes in GPR signal for detection. The HMM algorithm, on the other hand, is a feature based technique that relies on hyperbolic signatures to detect landmines. When fusing the detection confidences of the two algorithms properly, the performance is improved dramatically. The detection performance after fusion is demonstrated using data measured at a prepare test site during February and June 2000. Similar diagonal features used in HMM have been implemented and fused with EBP algorithm. Official offline scoring shows that the MH/K exit criteria of 92 percent Pd at 0.013/m2 FAR is met.
The Mine Hunter/Killer Close-In Detector (MH/K CID) uses Ground Penetrating Radar (GPR) as it's primary sensor. The GPR processor requires a sensitive detection algorithm to detect anomalies that may indicate the presence of a buried land mine. A general formula for a statistical detector is presented, consisting of a median filter to eliminate outliers, a local mean estimator using a Blackman window and a local covariance estimator. Advanced methods for robust estimation of the covariance matrix are presented and evaluated using data collected by the CID over buried land mines. This GPR detector is used as a preprocessor for image processing and mine classification algorithms that are used by a sensor fusion processor to determine when to activate the 'Killer' mechanism to neutralize the buried mine.
The Close-in Detection (CID) System is the vehicle-mounted multisensor landmine detection system for the Army CECOM Night Vision Electronic Sensors Directorate (NVESD) Mine Hunter/Killer (MH/K) Program. The CID System is being developed by BAE Systems in San Diego, CA. TRW Systems and Information Technology Group in Arlington, VA and a team of specialists for ERIM, E-OIR, SNL, and APL/JHU support NVESD in the development, analysis and testing of the CID and associated signal and data processing. The CID System includes tow down-looking sensor arrays: a ground- penetrating radar (GPR) array, and a set of Electro-Magnetic Induction (EMI) coils for metal detection. These arrays span a 3-meter wide swath in front of a high mobility, multipurpose wheeled vehicle. The system also includes a forward looking IR imaging system mounted on the roof of the vehicle and covering a swath of the road ahead of the vehicle. Signals from each sensor are processed separately to detect and localize objects of interest. Features of candidate objects are integrated in a processor that uses them to discriminates between anti-tank miens and clutter. Mine locations are passed to the neutralization subsystem of MH/K. This paper reviews the design of the sensors and signal processing of the CID system and gives examples and analysis of recent test results at the NVESD mine lanes. The strengths and weaknesses of each sensor are discussed, and the application of multisensor fusion is illustrated.
Marconi INtegrated Systems, formerly GDE Systems, Inc., has developed a rugged, lightweight, compact Vehicle Mounted Mine Detection (VMMD) system. Our VMMD system has Ground Penetrating Radar, Metal Detection, and IR sensors. Test results from the Army's VMMD Advanced Technology Demonstration (ATD) are presented and we show how results can be improved using post ATD improvements. Finally, we show the feasibility of integrating our sensor suite with an overpass capable and blast protected vehicle to make a battlefield capable detection syste.
This paper describes a vehicular mine detection system which automatically detects and marks buried land mines using very recent breakthroughs in mine detection technology. It combines proven detection technologies to realize a near 100% probability of detection for anti-tank mines. The detection system utilizes information from forward looking thermal and imaging system with downward looking radar and inductive pulse metal detection to sense the presence of buried or obscured land mines. Detection subsystems include: a sensor module, system processor, geographic location module and a real-time mine marking system. It also contains a registration process module which brings all selected targets, either in pixel space or sensor array position, to common platform coordinates, which in turn, are referenced to earth coordinates through GPS tracking of the platform. This registration process is extremely important, especially when integrating IR images from cameras whose positions are in non- nadir orientations. The detection system output provides geographic location of target mines, depth information, approximate mine shape and size, a natural scene image with graphically annotated mine locations.
The Balanced Bridge (BB) detection concept was developed just after the end of WWII. It has been researched for many years since then but it has never truly overcome the following inherent problems: sensitivity to antenna height and tilt variations, detectability of flush mines, sensitivity to soil moisture content, high false alarms, and most importantly, the inability to detect small anti-personnel (AP) mines. Even with all of these shortcomings, the BB sensor technology is still one of the most promising electrmagnetic mine detection systems. This paper will address a new BB detector and its preliminary field performance compared to earlier BB research. The new BB detector has superior capabilities compared to earlier BB efforts involving single frequency or single octave excitation because the new BB operates over a multi-octave bandwidth. The new BB detector also incorporates audio and visual presentations of digitally processed signals where earlier versions only had an audible announcement derived from a simple thresholding algorithm. New BB designs addressing previous BB deficiencies will also be discussed. Design changes include using a broadband printed circuit board antenna, RF transmit and receive components, and a digital signal processor. This new BB detector will be tested at an Advanced Technology Demonstration (ATD) evaluation in FY95. The ATD exit criteria will be discussed and compared to recent field testing of the new BB detector. Preliminary results with the new BB system have demonstrated encouraging results which will be incorporated in this paper.