The detection ofland mines has two fundamental goals: The first is a high detection rate (low probability of missing a mine) and the second is a low false alarm rate. Detection of mines and mine-like objects is generally not difficult; the problem is the high false-alarm rate caused by detection of innocuous objects such as shrapnel or metal junk, or even rocks or voids in the soil. The problem is one of discrimination, not one of detection. In order to maximize the success of achieving this goal, a mine detector needs to incorporate many complementary sensor technologies and to utilize the concept ofsensor data fusion. Two subsystems employ new signal processing techniques which extract certain features from the data that are unique identifiers ofthe mines. These features are the natural magnetic and electromagnetic resonances, which form the impulse response function, or equivalently, the natural frequencies represented by poles in the complex frequency plane. For different objects these are sufficiently distinct that pattern recognition processes can be used to arrive at a probability ofa match to a particular mine.
The measurement of electromagnetic fields and related quantities in a lightning environment is a challenging problem, especially at high frequencies and/or in the immediate vicinity of the lightning arcs and corona. This paper reviews the techniques for accomplishing such measurements in these regimes with examples. These sensors are often the same as for the nuclear electromagnetic pulse (EMP), but significant differences also appear.
Metal land mines still account for a large percentage of land mines, even with the advent of the so-called plastic mines. The metal detector thus remains a viable tool in the mine detector's bag. The limitation of the metal detector is not in detection of the mines, but in the additional detection of metal clutter. A metal detector has been developed which can largely discriminate the mines from the clutter, thereby greatly reducing false alarm rates. This "mine detector" is designed to characterize the magnetic polarizability dyadic of the metal objects, and to use pattern recognition to determine the goodness-of-fit to the responses of known mines. Data are presented from test runs conducted for the US Army for buried metal mines. Data are also presented for some non-mine metal targets. The characterization of the mines as threats is performed in a totally autonomous system, with high probability-of-detection and low false alarm rate. We can also generally tell one mine type from another.
Abstract-We introduce a combination of high-dimensional analysis of variance (HANOVA) and sequential probability ratio test (SPRT) to detect buried objects from an array ground-penetrating radar (GPR) surveying a region of interest in a progressive manner. Using HANOVA, we exploit the transient characteristic of GPR signals in the time domain to extract information about buried objects at fixed positions of the array. Based on the output of the HANOVA, the SPRT is employed to make detection decisions recursively as the array moves downtrack. The method is on-line implementable and of low computational complexity. Our approach is validated using field-data from two quite different GPR sensing systems designed for landmine detection applications.
The United States Army has contracted EG&G Technical Services to build the GSTAMIDS EMD Block 0. This system autonomously detects and marks buried anti-tank land mines from an unmanned vehicle. It consists of a remotely operated host vehicle, standard teleoperation system (STS) control, mine detection system (MDS) and a control vehicle. Two complete systems are being fabricated, along with a third MDS. The host vehicle for Block 0 is the South African Meerkat that has overpass capability for anti-tank mines, as well as armor anti-mine blast protection and ballistic protection. It is operated via the STS radio link from within the control vehicle. The Main Computer System (MCS), located in the control vehicle, receives sensor data from the MDS via a high speed radio link, processes and fuses the data to make a decision of a mine detection, and sends the information back to the host vehicle for a mark to be placed on the mine location. The MCS also has the capability to interface into the FBCB2 system via SINGARS radio. The GSTAMIDS operator station and the control vehicle communications system also connect to the MCS. The MDS sensors are mounted on the host vehicle and include Ground Penetrating Radar (GPR), Pulsed Magnetic Induction (PMI) metal detector, and (as an option) long-wave infrared (LWIR). A distributed processing architecture is used so that pre-processing is performed on data at the sensor level before transmission to the MCS, minimizing required throughput. Nine (9) channels each of GPR and PMI are mounted underneath the meerkat to provide a three-meter detection swath. Two IR cameras are mounted on the upper sides of the Meerkat, providing a field of view of the required swath with overlap underneath the vehicle. Also included on the host vehicle are an Internal Navigation System (INS), Global Positioning System (GPS), and radio communications for remote control and data transmission. The GSTAMIDS Block 0 is designed as a modular, expandable system with sufficient bandwidth and processing capability for incorporation of additional sensor systems in future Blocks. It is also designed to operate in adverse weather conditions and to be transportable around the world.
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