CAJ | 학술논문

该文利用了入射信号在空域的稀疏性，将波达方向（DOA）估计问题描述为在网格划分的空间协方差矩阵稀疏表示模型，并将其松弛为一个凸问题，从而提出了一种网格匹配下的交替迭代方法（AIEGM）。传统的基于稀疏重构的波达方向估计算法由于其模型的局限性，一旦入射角不在预先设定的离散化网格上，就会造成估计性能的急剧恶化。针对这个问题，该算法可以在离散化网格比较粗糙的前提下，通过交替迭代的方法求解一系列基追踪去噪（BPDN）问题，对于不在网格上的真实角度估计值进行修正，从而达到更精确的波达方向估计。仿真结果证明了 AIEGM算法的有效性。
해문이용료입사신호재공역적희소성，장파체방향（DOA）고계문제묘술위재망격화분적공간협방차구진희소표시모형，병장기송이위일개철문제，종이제출료일충망격필배하적교체질대방법（AIEGM）。전통적기우희소중구적파체방향고계산법유우기모형적국한성，일단입사각불재예선설정적리산화망격상，취회조성고계성능적급극악화。침대저개문제，해산법가이재리산화망격비교조조적전제하，통과교체질대적방법구해일계렬기추종거조（BPDN）문제，대우불재망격상적진실각도고계치진행수정，종이체도경정학적파체방향고계。방진결과증명료 AIEGM산법적유효성。
To estimate the true (unknown)directions which may not exactly fall on the preselected grid,a novel direction-of-arrival (DOA)estimation method based on the sparse spatial covariance model and the off-grid representation of the steering vector with Taylor expansion is presented.Utilizing the spatial sparse property of incident signals,this paper for-mulates the DOA estimation problem as an array covariance matrix sparse representation model in a discretized grid,and re-laxes the model as a convex problem.Thus,an alternating iterative estimator with grid matching (AIEGM)is proposed. Because of the limitations of grid-based model,the estimation performance of conventional methods based on sparse signal reconstruction can be highly deteriorated if the true directions of arrival are not on the preselected discretized grid.The pro-posed algorithm solves a series of basis pursuit denoising (BPDN)problems on a coarse grid for that problem,and revises the DOA estimation results to achieve higher estimation accuracy and has lower computational complexity than the existing off-grid DOA estimation methods.Simulation results confirm the efficacy of AIEGM.