| 摘要: |
| 针对传统稀疏阵列波达方向（DOA）估计算法在小快拍数、低信噪比和多信源数等条件下的估计精度不高的问题，提出了一种基于TOEPLITZ重构的压缩感知嵌套阵列DOA估计方法。首先利用TOEPLITZ重构方法将虚拟阵列的输出信号向量构建成满秩协方差矩阵，然后利用信号在空间域的稀疏性，将阵列协方差矩阵进行稀疏表示，通过噪声子空间和信号子空间的正交关系构建权值向量，对稀疏向量进行加权约束，最后通过求解最优化方程获取入射信源的DOA估计。仿真结果表明，本文方法比传统稀疏阵列DOA估计算法在低信噪比、小快拍数和多信源数下具有更好的DOA估计性能。 |
| 关键词: DOA估计 TOEPLITZ重构 嵌套阵列 稀疏表示 加权约束 |
| DOI：DOI:10.3969/j.issn.1672-2337.2024.03.013 |
| 分类号:TN911.7 |
| 基金项目:国家自然科学基金（No.61901332） |
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| DOA Estimation in Compressed Sensing Nested Array Based on TOEPLITZ Reconstruction |
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LI Ronglu， TANG Jianlong， YUAN Yongqiang
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School of Electronic Engineering, Xidian University, Xi’an 710071, China
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| Abstract: |
| In response to the limitations of traditional sparse array direction of arrival （DOA） estimation algorithms in scenarios with limited snapshots, low signal?to?noise ratio, and multiple sources, a compressed sensing nested array DOA estimation method based on TOEPLITZ reconstruction is proposed in this paper. Initially, the TOEPLITZ reconstruction method is used to construct a full?rank covariance matrix from the output signal vector of the virtual array. Subsequently, leveraging the spatial sparsity of signals, the array’s covariance matrix is represented sparsely. By exploiting the orthogonal relationship between noise and signal subspaces, a weight vector is constructed to impose weighted constraints on the sparse vector. Finally, the optimal equation is solved to estimate the DOA of incoming sources. The simulation results demonstrate the superior DOA estimation performance of the proposed method under conditions of low signal?to?noise ratio, limited snapshots, and multiple sources compared to traditional sparse array DOA estimation algorithms. |
| Key words: DOA estimation TOEPLITZ reconstruction nested array sparse representation weighted constraints |
