A time-varying clutter intensity estimation algorithm by using Gibbs sampler and BIC

In this paper, we consider clutter estimation issue under unknown, non-uniform and time-varying clutter background. First, we use finite mixture distributions (FMD) to fit the unknown clutter. As for the parameters of the FMD, we adopt the Gibbs sampler and Bayesian information criterion (BIC) to derive and evaluate clutter parameters. The final experiments show that the proposed algorithm can effectively deal with the unknown, non-uniform and time-varying clutter. Finally, a multi-target tracking example with unknown clutter intensity using random finite set filter is provided to verify the clutter estimation algorithm.