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ML-PMHT Track Detection Threshold Determination for K-Distributed Clutter Report Title Recentwork developed a novelmethod for determining tracking thresholds for theMaximumLikelihood ProbabilisticMultiHypothesis 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. Conference Name: SPIE Conf. Signal and Data Processing of Small Targets, #9092-23, Baltimore,MD, May 2014. Conference Date: May 15, 2014 2