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针对现有稀疏恢复算法在到达角(DOA)估计中存在的网格失配问题(即off-grid问题),提出基于连续稀疏恢复循环平稳信号的DOA估计。首先,对传统的谱相关信号子空间拟合算法进行分析研究;然后,在循环域利用连续稀疏恢复的思想来构造循环平稳信号的稀疏恢复模型。与传统Cyclic MUSIC算法和现有基于离散稀疏恢复算法相比,文中算法能够克服off-grid问题,具有较高的稀疏恢复精度和较好的稀疏恢复性能;同时,也适用于信号个数多于阵元个数的场合。理论分析和仿真实验证明了算法的有效性。
Aiming at the problem of grid mismatch (ie off-grid problem) existing in the DOA estimation of the existing sparse recovery algorithm, a DOA estimation based on continuous sparse recovery of cyclostationary signals is proposed. Firstly, the traditional spectrum-dependent signal subspace fitting algorithm is analyzed and studied. Then, the sparse recovery model of cyclic stationary signal is constructed using the idea of continuous sparse recovery in the circular domain. Compared with the traditional Cyclic MUSIC algorithm and the existing discrete sparse recovery algorithm, the proposed algorithm overcomes the off-grid problem, has higher sparse recovery accuracy and better sparse recovery performance, and also applies to more than The number of elements of the occasion. Theoretical analysis and simulation experiments show the effectiveness of the algorithm.