ML-PMHT track detection threshold determination for K-distributed clutter

Steven Schoenecker; Peter Willett; Yaakov Bar-Shalom

doi:10.1117/12.2049420

13 June 2014 ML-PMHT track detection threshold determination for K-distributed clutter

Steven Schoenecker, Peter Willett, Yaakov Bar-Shalom

Proceedings Volume 9092, Signal and Data Processing of Small Targets 2014; 90920M (2014) https://doi.org/10.1117/12.2049420
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

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.

Citation Download Citation

Steven Schoenecker, Peter Willett, and Yaakov Bar-Shalom "ML-PMHT track detection threshold determination for K-distributed clutter", Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 90920M (13 June 2014); https://doi.org/10.1117/12.2049420

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