Space Time Adaptive Parameter Estimation of Moving Target Based on Compressed Sensing

In this paper, by exploiting the intrinsic sparsity of the moving target in the angle-Doppler domain, a new space time adaptive moving target parameter estimation algorithm is proposed, which uses the technique of sparse recovery to estimate space-time parameter of the moving target. To solve the contradiction between the successful of sparse recovery probability and the higher resolution, a small dictionary is selected to keep the coherence value between every two adjacent columns of the dictionary equal to minimize, and the parameter estimated from the above sparse recovery is regard as a rough result. To obtain a more precise result, a following match filter is applied to the local neighborhood of the obtained rough value. Effectiveness of the new method is verified via simulation examples.