Radar Detection and Tracking of Targets in the Presence of Clutter Edge via DP-TBD

In this paper, we focus on the performance improvement of dynamic programming based track-before-detect (DP-TBD) in heterogeneous Rayleigh background, in which case the surveillance scene is divided into two parts with separate independent and identically distributed Rayleigh probability density functions. Original DP-TBD (DP-TBD using signal amplitude scoring function) suffers significant performance loss under this condition. Optimal DP-TBD (DP-TBD using log-likelihood ratio (LLR) scoring function) usually can not be obtained since the clutter edge position and clutter statistics are unknown. To overcome these challenges, we propose an improved DPTBD strategy, which applies a data pre-processing step to the measurement frame before DP processing, the clutter is then suppressed. Simulation results show that the proposed DP-TBD outperforms the original DP-TBD, the false tracks is reduced over 80%, and the performance loss is less than 0.5dB in comparison with the optimal DP-TBD.