阵列通道不一致性误差快速有源校正算法

Fast Active Error Calibration Algorithm for Array Chanel Uncertainty

针对阵列通道不一致性引起的幅相误差校正问题,基于多级维纳滤波器(MSWF),该文提出幅相误差快速校正的简化的多级维纳滤波器(SMSWF)算法。SMSWF算法利用校正源的方位和波形信息对阵列幅相参数进行估计,无需估计协方差矩阵和进行特征值分解,大大地减小了计算量,且具有与特征分解方法相同的幅相参数估计性能。研究发现,单个信源入射到阵列且信源波形已知时,SMSWF算法获得的信号子空间等价于特征分解法得到的信号子空间,这表明SMSWF算法能够替代特征分解法,从而极大减小基于特征分解法的信号处理方法的计算量。大量计算机仿真和消声水池试验验证了SMSWF算法的优越性能。

Aiming the error calibration for the array channel uncertainty, a new fast algorithm named Simplified Multi-Stage Wiener Filter（SMSWF） based on the Multi-Stage Wiener Filter（MSWF） is proposed. The SMSWF takes the advantages of the DOA and the waveform of the cooperative source to estimate the gain and the phase factors, and it does not need to estimate the covariance matrix and the eigendecomposition operations. Compared with the eigendecomposition algorithm, the SMSWF has the same performance for estimating gain and phase factors while greatly reduce the complexity. The researches show that if a single source with a known waveform incidence on the array, the signal subspaces obtained by the SMSWF and one obtained by the eigendecomposition are equipollent, which demonstrate that the SMSWF is able to replace the eigendecomposition. The complexity of signal processing methods based on the eigendecomposition can greatly be reduced by replacing the eigendecomposition with the SMSWF. The extensive computer simulations and experiment in anechoice water tank show the superiori performance of the proposed algorithm.