Abstract
A test statistic, which does not require prior knowledge of, is proposed to support automatic track confirmation and termination decisions in a multiple hypotheses tracker (MHT). Use of gamma distributions yields a linear log-likelihood ratio (LLR) with constant parameters derived from target and clutter models. The proposed LLR results in a higher probability of true track confirmation (i.e., the statistical power of the test) for a given probability of false track confirmation than does the reference MHT implementation and more uniform confirmation statistics.
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