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Proceedings Paper

ML-PMHT track detection threshold determination for K-distributed clutter
Author(s): Steven Schoenecker; Peter Willett; Yaakov Bar-Shalom
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Paper Abstract

Recentwork developed a novelmethod for determining tracking thresholds for theMaximumLikelihood ProbabilisticMulti- Hypothesis Tracker (ML-PMHT). Under certain “ideal” conditions, probability density functions (PDFs) for the peak points in the ML-PMHT log-likelihood ratio (LLR) due to just clutter measurements could be calculated. Analysis of these clutter-induced peak PDFs allowed for the calculation of tracking thresholds, which previously had to be donewith time-consumingMonte Carlo simulations. However, this work was done for a very specific case: the amplitudes of both target and cluttermeasurements followed Rayleigh distributions. The Rayleigh distribution is a very light-tailed distribution, and it can be overly optimistic in predicting that high-SNR measurements are target-originated. This work examines the case where the clutter amplitudes do not follow a Rayleigh distribution at all, but instead follow a K-distribution, which more accurately describes active acoustic clutter. This will provide a framework for determining accurate tracking thresholds for the ML-PMHT algorithm.

Paper Details

Date Published: 13 June 2014
PDF: 9 pages
Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 90920M (13 June 2014); doi: 10.1117/12.2049420
Show Author Affiliations
Steven Schoenecker, Naval Undersea Warfare Ctr. (United States)
Peter Willett, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 9092:
Signal and Data Processing of Small Targets 2014
Oliver E. Drummond, Editor(s)

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