针对 MUSIC 算法和基于四阶累积量的 MUSIC-like 算法在高斯色噪声背景下测向精度不理想的问题，提出基于延时相关的稀疏恢复高分辨来波方位估计算法。该算法利用蕴含在接收数据延时相关函数中的角度信息，采用所有阵元接收数据的延时相关函数构造新的阵列输出矩阵，进而构造新的协方差矩阵，并进行奇异值分解，建立稀疏表示模型，使用l1范数法对稀疏模型进行求解实现色噪声环境下高分辨 DOA估计。仿真实验表明，基于延时相关的稀疏表示模型的测向分辨率好于基于传统子空间的 MUSIC 算法和基于四阶累积量的 MUSIC-like算法，能降低协方差构造的复杂度，增强色噪声抑制能力。%In order to solve theproblem of angular precision of DOA estimation of MUSIC algorithm and MU-SIC-like algorithm in the background of Gaussian color noise,an approach for high resolution DOA estimation based on sparse reconstruction of the delay correlation function of the received data preprocessing was proposed. The proposed algorithm made full use of the information of the direction of arrival contained in the delay correla-tion function and used the delay correlation function of all the received data to construct a new array matrix,then through the singular value decomposition to construct the sparse representation model and using l1 norm algo-rithm to realize high resolution DOA estimation in the background of Gaussian color noise.The proposed algo-rithm had lower covariance computational complexity and good ability to restrain Gaussian color noise.Experi-mental results showed that the resolution DOA estimation of sparse representation model based on time delay correlation function had a better performance than MUSIC algorithm based on the traditional subspace and MU-SIC-like algorithm based on fourth-order cumulant.
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