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A track-before-detect labelled multi-Bernoulli particle filter with label switching (1604.00082v1)
Published 31 Mar 2016 in stat.AP and cs.SY
Abstract: This paper presents a multitarget tracking particle filter (PF) for general track-before-detect measurement models. The PF is presented in the random finite set framework and uses a labelled multi-Bernoulli approximation. We also present a label switching improvement algorithm based on Markov chain Monte Carlo that is expected to increase filter performance if targets get in close proximity for a sufficiently long time. The PF is tested in two challenging numerical examples.