
Proceedings Paper
Upper bound on false alarm rate for landmine detection and classification using syntactic pattern recognitionFormat | Member Price | Non-Member Price |
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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
Published in SPIE Proceedings Vol. 7664:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV
Russell S. Harmon; John H. Holloway Jr.; J. Thomas Broach, Editor(s)
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)
Brian L. Mark, George Mason Univ. (United States)
Kenneth J. Hintz, George Mason Univ. (United States)
Nathalia Peixoto, 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 Jr.; J. Thomas Broach, Editor(s)
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