22 July 1997 Detecting regularity in minefields using collinearity and a modified Euclidean algorithm
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Minefields have point patterns that tend to exhibit regularity such as equal-spacing and collinearity that provide potentially valuable discriminants against natural occurring clutter. Previously, several simple procedures based on the empty boxes test and its extensions have ben shown to be effective detectors of generic regularity in minefields without explicitly taking advantage of collinearity and equal-spacing. Recently, modifications of the Euclidean algorithm have been applied to the problem of determining the period from a sparse set of detection times which arises in pulse repetition interval analysis. Besides the intriguing properties of this approach because of its number theoretic roots, the resulting algorithms are both computationally efficient and robust to errors introduced by missed detections, noise in time location, and false alarms. In this paper, a two-step procedure for detecting minefields is proposed whereby collinear points are first detected using a standard approach, the Hough transform, and the period estimated using the modified Euclidean algorithm. One advantage of this approach is that prior information on minefield spacing can be utilized to exclude collinear points that do not exhibit any periodicity or are spaced too close together or too far apart. The preliminary detection performance of some of these minefield detection methods are quantified for using a point pattern extracted from real sensor data.
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Douglas E. Lake, Douglas E. Lake, Brian M. Sadler, Brian M. Sadler, Stephen D. Casey, Stephen D. Casey, "Detecting regularity in minefields using collinearity and a modified Euclidean algorithm", Proc. SPIE 3079, Detection and Remediation Technologies for Mines and Minelike Targets II, (22 July 1997); doi: 10.1117/12.280878; https://doi.org/10.1117/12.280878

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