声矢量阵自适应抵消稳健波束形成算法

摘要

The standard adaptive beamformer seriously suffers from performance degradation in the presence of mis-matching errors between the actual and presumed steering. In order to improve the detection ability of the passive sonar,a novel robust adaptive beamforming algorithm combined with adaptive canceling using a vector sensor is proposed. Firstly,the null of each unit was adjusted to the maximum direction of the beamformer by combining the acoustic pressure and particle velocity,and the outputs were regarded as the reference signals of the adaptive cance-ling to suppress the desired signal in the received data;then the eigenvalues in the noise subspace were smoothed by the eigen-decomposition of the covariance matrix;finally,the weight vector of the adaptive beamformer was com-puted using a reconstructed covariance matrix. Both the theoretical analysis and computer simulations show that the new method can efficiently improve the robustness of the adaptive beamforming algorithm based on the acoustic vec-tor sensor array because the reconstructed covariance matrix only consists of coherent interference and noise. The output SINR was satisfactory even in the condition of a large steering vector error or high SNR.%常规自适应波束形成算法在期望信号导向矢量存在误差时，性能严重下降。为了改善被动声呐的探测能力，结合声矢量自适应抵消技术，提出了一种新的稳健自适应波束形成算法。通过组合声压和振速分量在波束方向上形成零点，并以之作为自适应抵消的参考输入，去除接收数据中的期望信号成分；然后对协方差矩阵进行特征分解，平滑噪声子空间的特征值；最后利用重构的协方差矩阵求解自适应波束形成的权向量。理论分析和仿真结果表明，新算法重构出的协方差矩阵仅包含干扰和噪声，显著改善了声矢量阵自适应波束形成的稳健性，在期望信号存在大的阵列流形误差和高信噪比情况下，都能给出令人满意的输出信干噪比。