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Proceedings Paper

Extremal methods in mine detection and classification
Author(s): M. Ross Leadbetter
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Paper 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.

Paper Details

Date Published: 20 June 1995
PDF: 8 pages
Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); doi: 10.1117/12.211363
Show Author Affiliations
M. Ross Leadbetter, Univ. of North Carolina/Chapel Hill (United States)

Published in SPIE Proceedings Vol. 2496:
Detection Technologies for Mines and Minelike Targets
Abinash C. Dubey; Ivan Cindrich; James M. Ralston; Kelly A. Rigano, Editor(s)

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