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Proceedings Paper

Performance results of the bi-level multiple hypothesis tracking (MHT) algorithm for two crossing targets in a high-clutter environment
Author(s): David S.K. Chan; David A. Langan
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Paper Abstract

The future need to detect and track low-observable targets against clutter backgrounds means that the track processor will be required to cope with much higher false detection rates than can be handled by traditional `zero-scan' tracking algorithms. We have developed a Bi-Level MHT algorithm which is capable of tracking in such a demanding environment. This paper provides an update to this previously reported algorithm, and extends previously reported single-target performance results to the case of two crossing targets. Specifically, we present Monte Carlo simulation results characterizing the ability of the algorithm to hold onto two target tracks as they cross, under a range of false detection densities. We will also assess the loss in performance due to target interaction, as well as gain in performance obtained from propagating multiple hypothesis. Finally, we will give an indication of computational complexity by measuring various operation counts as a function of false detection density.

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: 10.1117/12.179067
Show Author Affiliations
David S.K. Chan, GE Corporate Research and Development Ctr. (United States)
David A. Langan, GE Corporate Research and Development Ctr. (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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