Adaptive Sensing for Improving Detection of Unexploded Ordnances with a Sigma-Point Information Filter

Alan Y. Chen

Abstract:	Unexploded ordnances (UXOs) are a significant problemin this country and in the world because of their dangerous nature and their environmental impact. They are often buried in unknown locations, and therefore need to be found so they can be excavated. Currently, a major focus of UXO related research is reducing the large number of false positive detections for every true positive detection. This paper further develops a strategy previously proposed by the author. The concept proposed adds a new step to the current UXO detection and localization strategy. This step aims to reduce the number of false positives by improving the efficiency and the information gathered on a potential UXO. This is made possible by using a GNSS equipped vehicle that traverses a suboptimal trajectory designed to maximize the amount of information an UXO sensor will obtain when reexamining a suspected UXO location. These new GNSS tagged measurements are then post-processed to more accurately detect and localize UXOs. This paper incorporates a sigma-point information filter into that original adaptive sensing technique. This filter combines the scalability of the information filter with the nonlinear attributes of the sigma-point Kalman filter. Using a range sensor, the sigma-point information filter approach is compared to an extended information filter approach. A total field magnetometer is then used with the adaptive sensing technique in simulation. The results show that the adaptive sensing approach out performs other traverse techniques in UXO localization and in gathering information. Hopefully, this information can later be used to help discriminate true positives from false positives.
Published in:	Proceedings of the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2008) September 16 - 19, 2008 Savannah International Convention Center Savannah, GA
Pages:	826 - 836
Cite this article:	Chen, Alan Y., "Adaptive Sensing for Improving Detection of Unexploded Ordnances with a Sigma-Point Information Filter," Proceedings of the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2008), Savannah, GA, September 2008, pp. 826-836.
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