A track-before-detect labelled multi-Bernoulli particle filter with   label switching
  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. 
\'Angel F. Garc\'ia-Fern\'andez
stat.AP cs.SY