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Proceedings Paper

Multisensor probabilistic multihypothesis tracking using dissimilar sensors
Author(s): Mark L. Krieg; Douglas A. Gray
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Paper Abstract

A difficult problem in multisensor and multi-tracking is that of data association. A multitarget tracking algorithm, probabilistic multi-hypothesis tracking (PMHT), overcomes this problem by estimating the measurement-to-target assignments and the target states simultaneously. We have previously developed two multi-sensor variations of this algorithm, the multi-sensor PMHT and the general multi- sensor PMHT. In this paper, we apply the multi-sensor PMHT algorithm to non-simultaneous radar and optical real data, recorded from a testbed consisting of a radar and optical sensor. Its performance in a multi-target environment is compared to that of a multi-sensor variable update rate Kalman filter.

Paper Details

Date Published: 23 June 1997
PDF: 10 pages
Proc. SPIE 3086, Acquisition, Tracking, and Pointing XI, (23 June 1997); doi: 10.1117/12.277181
Show Author Affiliations
Mark L. Krieg, Defence Science and Technology Organisation, Cooperative Research Ctr., and Univ. of Adela (Australia)
Douglas A. Gray, Cooperative Research Ctr. and Univ. of Adelaide (Australia)

Published in SPIE Proceedings Vol. 3086:
Acquisition, Tracking, and Pointing XI
Michael K. Masten; Larry A. Stockum, Editor(s)

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