Statistical fusion of GPR and EMI data

Robert A. Weisenseel; William Clement Karl; David A. Castanon; Eric L. Miller; Carey M. Rappaport; Charles A. DiMarzio

doi:10.1117/12.356998

2 August 1999 Statistical fusion of GPR and EMI data

Robert A. Weisenseel, William Clement Karl, David A. Castanon, Eric L. Miller, Carey M. Rappaport, Charles A. DiMarzio

Proceedings Volume 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV; (1999) https://doi.org/10.1117/12.356998
Event: AeroSense '99, 1999, Orlando, FL, United States

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.

Citation Download Citation

Robert A. Weisenseel, William Clement Karl, David A. Castanon, Eric L. Miller, Carey M. Rappaport, and Charles A. DiMarzio "Statistical fusion of GPR and EMI data", Proc. SPIE 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, (2 August 1999); https://doi.org/10.1117/12.356998

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