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Proceedings Paper

Source separation using sparse-solution linear solvers
Author(s): Jonathan T. Miller; Dean Keiswetter; Jim Kingdon; Tom Furuya; Bruce Barrow; Tom Bell
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Paper Abstract

An algorithm is proposed to enumerate, locate and characterize individual signal sources given observation of their combined signals. No a-priori estimate for the number of sources is required. We assume a forward model exists, and that superposition holds, i.e. coupling between sources is ignored. A system of linear equations y=Ax is set up in which columns of matrix A contain expected signals from a large number of hypothesized sources, and y contains the observed signal. Recently-developed solvers designed for linear systems with sparse non-negative solutions make this approach feasible even when large numbers of sources are involved. With each iteration, the collection of hypothesized sources is refined using a Harmony Search algorithm. Application is demonstrated on the problem of locating multiple buried conductors based on electromagnetic induction (EMI) signals observed at ground surface.

Paper Details

Date Published: 29 April 2010
PDF: 8 pages
Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 766409 (29 April 2010); doi: 10.1117/12.850412
Show Author Affiliations
Jonathan T. Miller, SAIC (United States)
Dean Keiswetter, SAIC (United States)
Jim Kingdon, SAIC (United States)
Tom Furuya, SAIC (United States)
Bruce Barrow, SAIC (United States)
Tom Bell, SAIC (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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