In order to improve the performance of sparse array direction of arrival(DOA)estimation,this paper applies low-rank matrix reconstruction theory to DOA estimation,and proposes an improved matrix completion model and its optimized solution method.This method uses the Sigmoid function to achieve the nuclear norm constraint and establishes a minimization model,and then based on the particle swarm algorithm to improve the augmented Lagrange multiplier method to achieve low-rank optimization solution to the model,and finally uses multiple signal classification(MUSIC)algorithm to realize the DOA estimation.The simulation results show that the method can effectively realize the reconstruction of sparse array,the performance of DOA estimation is excellent,and it can be applied to related information sources.
关键词
波达方向估计/稀疏阵列/矩阵填充/增广拉格朗日乘子法/粒子群寻优算法
Key words
direction of arrival estimation/sparse array/matrix completion/augmented Lagrange multiplier method/particle swarm optimization algorithm
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