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Proceedings Paper

Data fusion of association hypotheses in a distributed sensor network
Author(s): Craig S. Agate; Ronald A. Iltis
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Paper Abstract

A fusion algorithm is presented for a multisensor tracking system, in which the local trackers are N-scan data association filters. Previously, a fusion algorithm was given for the case where the local trackers are JPDA filters. Here, a fusion algorithm is presented for the more general case of local N-scan data association filters, of which the JPDA is a special case (N equals 0). The fusion equations consist of a simultaneous updating of the global hypothesis probabilities, and conditional global target state estimates. Two communication schemes between the local trackers and global processor are considered. A unidirectional communication scheme is examined in which the local trackers send the updated hypothesis probabilities and conditional target state estimates to the global processor; the local nodes then continue to track without knowledge of the global estimates. A bidirectional communication scheme is examined in which the local trackers send the updated hypothesis probabilities and conditional target state estimates to the global processor.

Paper Details

Date Published: 6 July 1994
PDF: 11 pages
Proc. SPIE 2235, Signal and Data Processing of Small Targets 1994, (6 July 1994); doi: 10.1117/12.179073
Show Author Affiliations
Craig S. Agate, Univ. of California/Santa Barbara (United States)
Ronald A. Iltis, Univ. of California/Santa Barbara (United States)


Published in SPIE Proceedings Vol. 2235:
Signal and Data Processing of Small Targets 1994
Oliver E. Drummond, Editor(s)

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