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20 June 1995 Extremal methods in mine detection and classification
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Abstract
This paper concerns general statistical properties of mine detection systems utilizing high (e.g. acoustic) returns in the presence of reverberation, modeled as a (background) random field. Recently developed extensions of the 1D theory of high level stochastic excursions are used to describe the occurrences of high peaks of a 2D background reverberation field by a (theoretically justified) Poisson model. This model and its further refinements are then used in discussing false alarm, detection, and classification probabilites.
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M. Ross Leadbetter "Extremal methods in mine detection and classification", Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); https://doi.org/10.1117/12.211363
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