An improved tbd algorithm based on dynamic programming for dim SAR target detection

Under the condition of low signal to clutter ratio, track-before-detect algorithm (TBD) based on dynamic programming (DP) can detect ground dim SAR moving targets. However, target diffusion and strong clutter in the background may result in high false alarm rate and low detection rate in the accumulation processing of TBD, so this paper proposes the state-weighted DP-TBD. The method utilizes the characteristic that displacement of the moving target is nearly equal between adjacent frames. When states in the kth frame are accumulated, we use accumulation information between the (k-1)th and (k-2)th to add a weight value to merit function in search window of the (k-1)th so that the target can accumulate along the real trajectory better. After accumulation, we can obtain the detection result through morphological processing. Simulation results show that the method in this paper can improve the detection performance in low signal-to-clutter ratio.