Research On DOA Estimation Method Based On Moving Sparse Nested Array

Direction of Arrival(DOA)estimation,as one of the main research directions in the field of array signal processing,can provide orientation information of target signal,and has a wide application prospect in electronic systems such as communication and radar.Traditional DOA estimation algorithm is mostly based on uniform linear array.Array aperture and degrees of freedom of uniform linear array is linearly constrained by the number of source signals,and there is a strong mutual coupling between arrays,which makes the performance of the above algorithm greatly restricted,and it is difficult to deal with complex signal scenes when the number of source signals is more than physical sensors.In recent years,the proposed nonuniform arrays(such as nested array/coprime array)can effectively enlarge array aperture and degree of freedom,and reduce the mutual coupling between physical sensors,so they have greater potential application.Based on this,in view of the above problems,we further expand nested array into sparse nested array.While realizing the DOA estimation under the underdetermined condition(i.e.,the number of source signals is more than physical sensors),we obtain larger array aperture to improve the estimation accuracy and adopt different algorithms to solve the fuzzy problem of DOA estimation caused by sparsity according to the signal scenes.The specific contents of this paper are as follows:(1)Moving sparse nested array based on multiple array-moves is proposed.In the above-mentioned array structure,the virtual array formed by moves replaces the physical sensors,and the sparse multiple determines the number of moves to ensure that the virtual array of the above-mentioned array is a uniform linear array.Based on this,DOA estimation algorithm based on discrete Fourier transform is adopted.The combination of the above-mentioned array and algorithm solves the fuzzy problem of DOA estimation and realizes the angle estimation under low computational complexity.(2)To achieve angle estimation in complex signal scenarios,a fast-moving sparse nested array based on single move and an improved DOA estimation algorithm based on non-uniform noise suppression and the processing of averaging accurate estimation value is proposed.Compared with the existing moving sparse nested array,the proposed array has larger array aperture and smaller mutual coupling,and at the same time,this two-component subarray which is structured by original array and virtual array by single-moved original array effectively reduces the array cost and time cost.The proposed algorithm can solve the fuzzy problem of DOA estimation caused by sparsity through this two-component subarray.In addition,the proposed algorithm can effectively reduce the influence of non-uniform noise and angle extraction on DOA estimation performance by replacing the elements of covariance matrix of the received data and the processing of averaging the elements of the subspace of the signal,and achieve a highly accurate and unique angle estimation.