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22 August 2000 Discrimination between buried metallic mines and metallic clutter using signal energy and exponential decay rates
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Abstract
An algorithm based on Bayesian probability theory is developed to discriminate buried metallic landmines from buried metallic clutter. A binary hypothesis problem is formed using the two hypotheses that the buried object is either a mine-like object or a clutter-like object. The received signal under both hypotheses is modeled as a target function, which is a delayed decaying exponential, plus Gaussian noise. The target functions contain the target's decay rate and coupling strength information. The coupling strength manifests itself as the point where the buried target's response reasons comes out of amplifier saturation. A target with a large coupling strength will fall out of saturation much later in time that a target with a low coupling strength. The decay rate for each buried object is extracted using a differential-corrections routine. The decay rate and fallout time are considered random variables with known distributions under each hypothesis. The distribution for the mine decay rates and fallout times are calculated from four separate measurements taken in a calibration area. The distribution of decay rates and fallout times for all objects in a blind grid is also estimated.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lloyd S. Riggs, Larry T. Lowe, James Elkins, Thomas Barnett, and Richard C. Weaver "Discrimination between buried metallic mines and metallic clutter using signal energy and exponential decay rates", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); https://doi.org/10.1117/12.396173
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