基于加权1范数稀疏信号重建的DoA估计

针对l₁范数下奇异值分解的l₁-SVD稀疏信号重建的波达方向估计方法存在求解量的稀疏性较差且空间谱中存在较多的伪峰，不能准确估计波达方向的问题，对接收信号矩阵进行预处理，并使用信号子空间设计权值矢量得到更好的稀疏性和更好地逼近l₀范数，利用得到的权值矢量对l₁-SVD算法中解矢量的各个元素进行加权，以得到的加权l₁范数作为最小化的目标函数进行优化.仿真结果表明，提出的算法在快拍数、正则化参数和信噪比等条件改变的情况下能有效抑制伪峰，并准确稳定地估计出波达方向.

DoA Estimation Based on Sparse Signal Recovery Utilizing Weighted 1 Norm

When l1-SVD algorithm is used for direction of arrival ( DoA) estimation with few snapshots and low signal noise ratio ( SNR) , there appear pseudo peaks in spatial spectrum, which lead to inaccu-rately DoA estimation results. To deal with this problem, the article proposes a DoA estimation method based on sparse signal recovery utilizing weighted 1 norm. Based on the sparse recovery, the weight vec-tor is chosen from the signal subspace and received signal matrix is multiplied. Then the product between weights and elements in the result is made to get weighted 1 norm is taken as target function for minimiza-tion. Simulations demonstrate that the proposed algorithm could effectively restrain the pseudo peak and accurately estimate the DoA under the different snapshots, regularization parameter and SNR.