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Proceedings Paper

Statistical fusion of GPR and EMI data
Author(s): Robert A. Weisenseel; William Clement Karl; David A. Castanon; Eric L. Miller; Carey M. Rappaport; Charles A. DiMarzio
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Paper Abstract

In this paper, we develop a statistical detection system exploiting sensor fusion for the detection of plastic A/P miens. We design and test the system using data from Monte Carlo electromagnetic induction (EMI) and ground penetrating radar (GPR) simulations. We include the effects of both random soil surface variability and sensor noise. In spite of the presence of a rough surface, we can obtain good result fusing EMI and GPR data using a statistical approach in a simple clutter environment. More generally, we develop a framework for simulation and testing of sensor configurations and sensor fusion approaches for landmine and unexploded ordinance detection systems. Exploiting accurate electromagnetic simulation, we develop a controlled environment for testing sensor fusion concepts, from varied sensor arrangements to detection algorithms, In this environment, we can examine the effect of changing mine structure, soil parameters, and sensor geometry on the sensor fusion problem. We can then generalize these results to produce mine detectors robust to real-world variations.

Paper Details

Date Published: 2 August 1999
PDF: 9 pages
Proc. SPIE 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, (2 August 1999); doi: 10.1117/12.356998
Show Author Affiliations
Robert A. Weisenseel, Boston Univ. (United States)
William Clement Karl, Boston Univ. (United States)
David A. Castanon, Boston Univ. (United States)
Eric L. Miller, Northeastern Univ. (United States)
Carey M. Rappaport, Northeastern Univ. (United States)
Charles A. DiMarzio, Northeastern Univ. (United States)


Published in SPIE Proceedings Vol. 3710:
Detection and Remediation Technologies for Mines and Minelike Targets IV
Abinash C. Dubey; James F. Harvey; J. Thomas Broach; Regina E. Dugan, Editor(s)

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