Robust generalized sidelobe canceller based on eigenanalysis and a MaxSINR beamformer

基于特征分析和最大信干噪比波束形成器的鲁棒广义旁瓣消除器（英文）

A robust generalized sidelobe canceller is proposed to combat direction of arrival(DOA)mismatches.To estimate the interference-plus-noise(IPN)statistics characteristics,conventional signal of interest(SOI)extraction methods usually collect a large number of segments where only the IPN signal is active.To avoid that collection procedure,we redesign the blocking matrix structure using an eigenanalysis method to reconstruct the IPN covariance matrix from the samples.Additionally,a modified eigenanalysis reconstruction method based on the rank-one matrix assumption is proposed to achieve a higher reconstruction accuracy.The blocking matrix is obtained by incorporating the effective reconstruction into the maximum signal-to-interferenceplus-noise ratio(MaxSINR)beamformer.It can minimize the influence of signal leakage and maximize the IPN power for further noise and interference suppression.Numerical results show that the two proposed methods achieve considerable improvements in terms of the output waveform SINR and correlation coefficients with the desired signal in the presence of a DOA mismatch and a limited number of snapshots.Compared to the first proposed method,the modified one can reduce the signal distortion even further.

提出一种鲁棒的广义旁瓣消除器抵抗到达方向失配的影响。为估计干扰加噪声的统计特性,传统信号提取方法常需收集大量仅存在干扰噪声的信号片段。为避免该收集过程,我们使用特征分析方法重新设计阻塞矩阵结构,从接收样本中重建干扰噪声的协方差矩阵。另外,基于秩-1矩阵假设,改进特征分析重建方法,以实现更高重建精度。将该重建方法与最大信干噪声比波束形成器结合,获得阻塞矩阵,最大限度减少信号泄漏的影响,并最大化干扰噪声功率,以进一步在最终输出中抑制噪声和干扰成分。数值结果表明,在存在到达方向失配和快照数有限的情况下,上述两种方法在输出波形信干噪比和与期望信号的相关系数方面有显著改进。与所提第一种方法相比,改进后的方法可进一步减少信号失真。