Range-Dependence Compensation Method for Bistatic STAP Radar

In this paper, we study the problem of detecting slow-moving targets using space-time adaptive processing (STAP). The construction of the optimum weights at each range implies the estimation of the interference-plus-noise covariance matrix. This is typically done by straight averaging of snapshots at neighboring ranges. However, in most bistatic configurations, snapshot statistics are range dependent. Straight averaging results thus in poor performance. This paper proposes a new method of obtaining an estimate of the covariance matrix using power spectrum registration based on nonuniform frequency sampling technique. Simulation results show a significant improvement in processor performance as compared to conventional STAP methods.