Maritime Targets Tracking in Heavy-tailed Clutter With Unknown and Time-varying Density

In order to solve the problem of maritime targets tracking in heavy-tailed sea clutter with unknown and time-varying clutter density, a multi-scan clutter sparsity estimator based amplitude-aided probability hypothesis density (MCSE-APHD) method is proposed in this paper. Firstly, the proposed method eliminates the target-originated measurements from multi-scan cumulative measurement set and estimates the spatial distribution density of clutter online. And the estimated clutter density parameter is fed to the tracker. Secondly, the amplitude-aided likelihood function as well as the estimated clutter parameter is established to update the Gaussian mixture posterior intensity of the state using the probability hypothesis density algorithm. The simulation results verify the effectiveness of the proposed algorithm.