A robust single data set-STAP algorithm

In this paper, a robust single data set-STAP (SDS-STAP) algorithm is proposed to against steering vector mismatch. Traditional STAP methods require a training data set which is usually absent in heterogeneous environment. In addition, the surrounding range cells do not possess the discrete jamming information of the test data (if existed) degrades the jamming suppression performance. The SDS-STAP methods, on the other hand, overcome these problems by operating solely on the test data. A novel algorithm based on the amplitude and phase estimation (APES) is introduced. It has a lower computational complexity and better clutter suppression performance than the other SDS-STAP methods. However, it is sensitive to steering vector mismatch caused by the inaccuracy knowledge of the direction of arrival and Doppler frequency. To overcome this problem, a Robust-APES algorithm which imposes two quadratic constraints and an iterative diagonally loaded is proposed to ensure the STAP response exceeds unity on a squared surface and prevent signal self-cancellation. Simulated and real data tests validate the effectiveness of the proposed method.