DOI: 10.26686/wgtn.16984759.v1
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State Estimation and  Smoothing for the  Probability Hypothesis  Density Filter

Abstract: <p>Tracking multiple objects is a challenging problem for an automated system, with applications in many domains. Typically the system must be able to represent the posterior distribution of the state of the targets, using a recursive algorithm that takes information from noisy measurements. However, in many important cases the number of targets is also unknown, and has also to be estimated from data. The Probability Hypothesis Density (PHD) filter is an effective approach for this problem. The method us… Show more

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