A robust reduced-rank monopulse algorithm based on variable-loaded MWF with spatial blocking broadening and automatic rank selection

作者：Qiu, Shuang; Sheng, Weixing^*; Ma, Xiaofeng; Han, Yubing; Zhang, Renli

来源：Digital Signal Processing, 2018, 78: 205-217.

DOI：10.1016/j.dsp.2018.02.015

• Multistage Wiener filter
• Spatial blocking broadening
• Variable loading
• Rank selection

For antenna array with large number of elements, the multistage Wiener filter (MWF) is an efficient method to perform reduced-rank beamforming. Similar to the generalized sidelobe canceller (GSC), MWF is also sensitive to direction of arrival (DOA) mismatch of the signal of interest (SOI). This condition limits the application of MWF to monopulse beamforming, in which the actual DOA of SOI may mismatch the assumed direction (i.e. the pattern look direction) due to target movement and platform disturbance. In this paper, we develop a variable-loaded multistage Wiener filter with spatial blocking broadening and automatic rank selection (VLSRS-MWF) to perform robust reduced-rank monopulse beamforming. Firstly, a null-broadened spatial blocking matrix which can be used for both the sum and difference beams is developed instead of the derivative constraints and the eigenvector constraints based blocking matrices. Secondly, a l(2)-norm regularization method is incorporated with MWF to further improve the output signal to noise ratio and to restrict the pattern sidelobe level. Then a Ritz value criterion with deterministic threshold for selecting the rank of the reduced-rank subspace is developed utilizing the eigenvalue distribution of sample covariance matrix and the Ritz value criterion. Simulation results show that the proposed VLSRS-MWF based monopulse algorithm can maintain good robustness and high angle estimation accuracy in presence of DOA mismatch.

• 出版日期2018-7
• 单位南京理工大学