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Proceedings Paper

Kalman filters applied to the detection of unexploded ordnance
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Paper Abstract

The detection of unexploded ordnance (UXO) in the electromagnetic induction regime often suffers from a low signal to noise ratio due to the strong decay of the magnetic field. As a result, a deep UXO may be overshadowed by smaller yet shallower metal items which render the classification of the main target challenging. It is therefore desirable to have the ability to model the various sources of noise and to include them in a detection algorithm. Toward this effect, we investigate here Kalman and extended Kalman filters for the inversion of UXO polarizabilities and positions, respectively, within a dipole model approximation. Inherent to the method, our analysis is based on the assumption of Gaussian noise distribution, which is often reasonable. Results are shown on both synthetic and TEMTADS data which have been purposely corrupted with noise. In particular, the situation of a main target in the presence of dense clutter is investigated, whereby the clutter is composed of 16 nosepieces buried close to the sensor.

Paper Details

Date Published: 28 April 2010
PDF: 9 pages
Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 766402 (28 April 2010); doi: 10.1117/12.848564
Show Author Affiliations
Tomasz M. Grzegorczyk, Delpsi, LLC (United States)
Benjamin Barrowes, U.S. Army Engineer Research and Development Ctr. (United States)
Fridon Shubitidze, Dartmouth College (United States)
Sky Research, Inc. (United States)
J. P. Fernández, Dartmouth College (United States)
Irma Shamatava, Dartmouth College (United States)
Kevin A. O'Neill, U.S. Army Engineer Research and Development Ctr. (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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