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基于联合稀疏矩阵恢复的思想,提出一种新的窄带信号DOA估计算法。算法通过对计算得到的各帧阵列协方差矩阵进行矢量化操作,构造伪数据矩阵;然后构建过完备的阵列方向矩阵字典,形成联合稀疏信号模型;接着利用联合l2,0逼近法求出联合稀疏矩阵的优化解,由此得到信号DOA的估计值。由于二阶统计量的矢量化操作扩展了阵列孔径,算法能够分辨多于阵元数的信号,同时适用于窄带短时平稳或平稳信号,且不需要预先估计信号源数。计算机仿真结果证明了算法的有效性。
Based on the idea of joint sparse matrix recovery, a new DOA estimation algorithm for narrowband signal is proposed. The algorithm constructs a pseudo-data matrix by vectorizing the calculated frame array covariance matrix, then constructs a complete dictionary of array orientation matrixes to form a joint sparse signal model, and then uses a joint l2,0 approximation method to obtain a joint sparse The optimal solution of the matrix, thus obtaining the estimated value of the signal DOA. Due to the vector operation of second-order statistics expanding the aperture of the array, the algorithm can distinguish more than the number of array elements and is suitable for narrow-band short-term stationary or stationary signals without the need to estimate the number of sources in advance. Computer simulation results prove the effectiveness of the algorithm.