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Proceedings Paper

Linear density algorithm for patterned minefield detection
Author(s): Robert R. Muise; Cheryl M. Smith
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Paper Abstract

Given a set of {(x,y)} coordinates, some corresponding to mine locations and the rest corresponding to the locations of minelike clutter, an algorithm is developed which attempts to recognize linear patterns in the data, to filter out clutter, and declare a region as being a minefield or not a minefield. A linear density is computed for each observation at multiple directions. High densities as well as frequently occurring directions are statistics computed for minefield detection as well as pattern recognition for locating minelines. Significance and power curves are developed by Monte Carlo simulation under the assumption that the observed clutter is distributed uniformly over the area scanned. Some limited results on real minefield data are then presented.

Paper Details

Date Published: 20 June 1995
PDF: 8 pages
Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); doi: 10.1117/12.211355
Show Author Affiliations
Robert R. Muise, Naval Surface Warfare Ctr. (United States)
Cheryl M. Smith, Naval Surface Warfare Ctr. (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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