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Proceedings Paper

Upper bound on false alarm rate for landmine detection and classification using syntactic pattern recognition
Author(s): Ahmed O. Nasif; Brian L. Mark; Kenneth J. Hintz; Nathalia Peixoto
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Paper Abstract

Recently, there has been considerable interest in the development of robust, cost-effective and high performance non-metallic landmine detection systems using ground penetrating radar (GPR). Many of the available solutions try to discriminate landmines from clutter by extracting some form of statistical or geometrical information from the raw GPR data, and oftentimes, it is difficult to assess the performance of such systems without performing extensive field experiments. In our approach, a landmine is characterized by a binary-valued string corresponding to its impedance discontinuity profile in the depth direction. This profile can be detected very quickly utilizing syntactic pattern recognition. Such an approach is expected to be very robust in terms of probability of detection (Pd) and low false alarm rates (FAR), since it exploits the inner structure of a landmine. In this paper, we develop a method to calculate an upper bound on the FAR, which is the probability of false alarm per unit area. First, we parameterize the number of possible mine patterns in terms of the number of impedance discontinuities, dither and noise. Then, a combinatorial enumeration technique is used to quantify the number of admissible strings. The upper bound on FAR is given as the ratio of an upper bound on the number of possible mine pattern strings to the number of admissible strings per unit area. The numerical results show that the upper bound is smaller than the FAR reported in the literature for a wide range of parameter choices.

Paper Details

Date Published: 29 April 2010
PDF: 12 pages
Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 76642G (29 April 2010); doi: 10.1117/12.852437
Show Author Affiliations
Ahmed O. Nasif, George Mason Univ. (United States)
Brian L. Mark, George Mason Univ. (United States)
Kenneth J. Hintz, George Mason Univ. (United States)
Nathalia Peixoto, George Mason Univ. (United States)


Published in SPIE Proceedings Vol. 7664:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV
Russell S. Harmon; John H. Holloway; J. Thomas Broach, Editor(s)

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