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Proceedings Paper

Randomized group testing for acoustic source localization
Author(s): William Mantzel; Justin Romberg; Karim Sabra
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Paper Abstract

Undersea localization requires a computationally expensive partial differential equation simulation to test each candidate hypothesis location via matched filter. We propose a method of batch testing that effectively yields a test sequence output of random combinations of location-specific matched filter correlations, such that the computational run time varies with the number of tests instead of the number of locations. We show that by finding the most likely location that could have accounted for these batch test outputs, we are able to perform almost as well as if we had computed each location's matched filter. In particular, we show that we can reliably resolve the target's location up to the resolution of incoherence using only logarithmically many measurements when the number of candidate locations is less than the dimension of the matched filter. In this way, our random mask pattern not only performs substantially the same as cleverly designed deterministic masks in classical batch testing scenarios, but also naturally extends to other scenarios when the design of such deterministic masks may be less obvious.

Paper Details

Date Published: 27 January 2010
PDF: 5 pages
Proc. SPIE 7533, Computational Imaging VIII, 753309 (27 January 2010); doi: 10.1117/12.848620
Show Author Affiliations
William Mantzel, Georgia Institue of Technology (United States)
Justin Romberg, Georgia Institue of Technology (United States)
Karim Sabra, Georgia Institue of Technology (United States)


Published in SPIE Proceedings Vol. 7533:
Computational Imaging VIII
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)

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