Data fusion of association hypotheses in a distributed sensor network

Craig S. Agate; Ronald A. Iltis

doi:10.1117/12.179073

6 July 1994 Data fusion of association hypotheses in a distributed sensor network

Craig S. Agate, Ronald A. Iltis

Proceedings Volume 2235, Signal and Data Processing of Small Targets 1994; (1994) https://doi.org/10.1117/12.179073
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

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.

Citation Download Citation

Craig S. Agate and Ronald A. Iltis "Data fusion of association hypotheses in a distributed sensor network", Proc. SPIE 2235, Signal and Data Processing of Small Targets 1994, (6 July 1994); https://doi.org/10.1117/12.179073

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KEYWORDS

Detection and tracking algorithms

Algorithm development

Data fusion

Computer simulations

Sensors

Monte Carlo methods

Electronic filtering

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