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Patterns in spatial point locations: Local indicators of spatial association in a minefield with clutter. (English) Zbl 1005.90555

Summary: The problem of detecting a minefield in the presence of clutter can be abstracted to that of detecting a spatial pattern within a set of point locations. The point locations are superpositions of several patterns, one of which corresponds to mines. In contrast to previous articles that take a formal, model-based approach, this article proposes a statistical methodology that is distinctly exploratory. Each point location is considered separately, and its contributions to a global measure of spatial distances between locations are featured. Different patterns and unusual points can be more easily identified on the new scale. Both minefield data and simulated point patterns demonstrate the power of the method.

MSC:

90C27 Combinatorial optimization
90B80 Discrete location and assignment
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[1] Anselin, Geogr Anal 27 pp 93– (1995) · doi:10.1111/j.1538-4632.1995.tb00338.x
[2] Byers, J Am Stat Assoc 93 pp 577– (1998)
[3] Inter-event distance methods for the statistical analysis of spatial point processes, Ph.D. Dissertation, Department of Statistics, University of Chicago, Chicago, IL, 1995.
[4] Collins, J Agric Biol Environ Stat 6 (2001)
[5] Cressie, Adv Appl Probab 32 pp 315– (2000)
[6] Statistical analysis of spatial point patterns, Academic, London, 1983. · Zbl 0559.62088
[7] Fiksel, Statistics 19 pp 67– (1988)
[8] Getis, Ecology 68 pp 473– (1987)
[9] Getis, Geogr Anal 24 pp 189– (1992) · doi:10.1111/j.1538-4632.1992.tb00261.x
[10] and ?Adaptive multispectral CFAR detection of land mines,? Detection technologies for mines and minelike targets, and (Editors), Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 2496, Bellingham, WA, 1995, pp. 421-432. · doi:10.1117/12.211339
[11] and Applied multivariate statistical analysis, Prentice Hall, Englewood Cliffs, NJ, 1992.
[12] and ?Detecting regularity in minefields using collinearity and a modified Euclidean algorithm,? Detection and remediation technologies for mines and minelike targets II, and (Editors), Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 3079, Bellingham, WA, 1997, pp. 500-507. · doi:10.1117/12.280878
[13] and Nonparametric minefield detection and localization, Technical Memorandum CSS TM591-91, Coastal Systems Station, Dahlgren Division, Naval Surface Warfare Center, Panama City, FL, 1992.
[14] and ?A linear density algorithm for pattern minefield detection,? Detection technologies for mines and minelike targets, and (Editors), Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 2496, Bellingham, WA, 1995, pp. 583-593.
[15] Ohser, Biometrical J 23 pp 523– (1981)
[16] and ?Exploiting stochastic partitions for minefield detection,? Detection and remediation technologies for mines and minelike targets II, and (Editors), Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 3079, Bellingham, WA, 1997, pp. 508-518. · doi:10.1117/12.280879
[17] Ripley, J Appl Probab 13 pp 255– (1976)
[18] Ripley, J Roy Stat Soc Ser B 39 pp 172– (1977)
[19] Density estimation for statistics and data analysis, Chapman and Hall, London, 1986. · Zbl 0617.62042 · doi:10.1007/978-1-4899-3324-9
[20] and Stochastic geometry and its applications, Wiley, Chichester, 1987.
[21] and Fractals, random shapes and point fields, Wiley, New York, 1994. · Zbl 0828.62085
[22] Stoyan, Biometrical J 38 pp 259– (1996)
[23] and Modern applied statistics with S-Plus, Springer-Verlag, New York, 1994. · doi:10.1007/978-1-4899-2819-1
[24] and ?The coastal battlefield reconnaissance and analysis (COBRA) program for minefield detection,? Detection technologies for mines and minelike targets, and (Editors), Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 2496, Bellingham, WA, 1995, pp. 500-508. · doi:10.1117/12.211346
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