Robust Space Time Adaptive Processing in Heterogeneous Environment

Abstract

Airborne phased array radar receives strong clutter when it detects ground moving target, and clutter seriously degrades the performance of target detection. Space time adaptive processing (STAP) is able to suppress clutter, while it needs training samples to estimate clutter covariance matrix. In heterogeneous interference environment, the covariance matrix cannot be well estimated and the performance of clutter suppression degrades. This paper proposes a method of covariance matrix estimation to improve the performance of STAP in heterogeneous interference environments. The method first discards training samples which may be contaminated by target signals. Then, the correlation coefficients of the cell under test and the remaining samples are estimated, and the coefficients are used as weighting coefficients to measure the contributions of the corresponding samples to the estimation of covariance matrix. The accuracy of the estimated covariance matrix can be improved significantly, and thus results in an evident performance improvement of STAP in heterogeneous environments. Experimental results demonstrate the effectiveness of the proposed method.