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Proceedings Paper

Multidimensional SME filter for multitarget tracking
Author(s): Douglas J. Muder; Sean D. O'Neil
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Paper Abstract

Kamen et al. have developed the symmetric measurement equation (SME) filter as an alternative to multi-target trackers based on data association. This paper presents an improved multi-dimensional SME tracking algorithm which agrees with Kamen's for one-dimensional scenarios and avoids the ghost target problem in higher dimensions. In addition, we provide a more efficient method for computing the noise covariance matrix of the SME coefficients. This was the major computational bottleneck of earlier SME implementation, and we have reduced its complexity from at least 2N/2 operations to at most D4N5, where N is the number of targets and D the number of dimensions. Computer simulations illustrate a failure mode that the new algorithm avoids, and gives a sample comparison to a standard data- association algorithm, global nearest neighbor.

Paper Details

Date Published: 22 October 1993
PDF: 13 pages
Proc. SPIE 1954, Signal and Data Processing of Small Targets 1993, (22 October 1993); doi: 10.1117/12.157789
Show Author Affiliations
Douglas J. Muder, MITRE Corp. (United States)
Sean D. O'Neil, MITRE Corp. (United States)

Published in SPIE Proceedings Vol. 1954:
Signal and Data Processing of Small Targets 1993
Oliver E. Drummond, Editor(s)

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