Mainlobe maintenance using shrinkage estimator method
Chenwei Sun, Haihong Tao, Jiaqi Song, Langxu Zhao · IET Signal Processing · 2017
A mainlobe maintenance method based on shrinkage estimator is presented here to promote the adaptive digital beamforming performance when there exists mainlobe jamming (MLJ). First, block matrix preprocessing (BMP) method is applied to suppress the MLJ. Then, the linear combination of estimated covariance matrix and identity matrix is optimised to generate more accurate estimation of the covariance matrix. After that, the improved covariance matrix is utilised to generate the adaptive weights to suppress the sidelobe jamming. Finally, the simulation shows that the proposed method is capable of eliminating peak offset of mainlobe and high sidelobes introduced by BMP and provides robustness against finite data samples effects. Accordingly, it outperforms noise whitening with error compensation, diagonal loading, and robust covariance matrix reconstruction in output SINR.