Sparse array DOA estimation technique based on matrix completion
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.
direction of arrival estimationsparse arraymatrix completionaugmented Lagrange multiplier methodparticle swarm optimization algorithm
万方数据
维普
