Study On Robust Beamforming For Sparse Array

Sparse array element spacing is usually larger than the half-wavelength of the carrier,which means that a sparse array can obtain a larger array aperture with the same number of physical elements than a traditional array,resulting in better resolution,thus saving hardware costs and reducing the computational complexity of the system.In recent years,many experts and scholars have made considerable progress in the direction estimation of sparse array,but the research on sparse array beamforming algorithm is still less,so it is meaningful to study this problem.This paper focus on the research of sparse array in the beamforming area,including the optimization of Robust Adaptive Beamforming(RAB)algorithm and its application in the coprime array.The main research contents of RAB beamforming can be summarized as follows:(1)This paper uses the uniform linear array as the research model.Aiming at the mismatch problem caused by the typical errors in the robust beamforming,this paper proposes two improved robust beamforming algorithms.The first robust beamforming algorithm is to reduce the covariance matrix estimation error and improve the anti mismatch performance of steering vector,the matrix shrinkage and super-resolution spectrum estimation are used to deal with the above two problems.The simulation results show that the algorithm has better robustness than the contrast algorithm.(2)In view of the desired components of the received signals in the array,a second robust beamforming algorithm is proposed,which is considered from the reconstruction of interference plus noise covariance matrix(INCM)and the estimation of the guidance vector.The INCM without desired components is obtained by using the equivalent subspace theory and the orthogonality of the guide vector,The desired signal covariance matrix is obtained by the same principle,and then the estimated value of the desired signal steering vector is obtained through the matrix.Simulation results show that the algorithm improves the accuracy of INCM reconstruction effectively,and the estimated steering vector is close to the ideal value,which makes the performance of the beamformer greatly improved.(3)Aiming at the existing robust beamforming algorithms for coprime arrays that do not fully utilize the excellent characteristics of coprime arrays,a coprime array robust beamforming algorithm based on Singular Value Thresholding(SVT)is proposed.The algorithm finds discontinuous locations in the differential optimization array,fills in0 to get a sparse covariance matrix,uses SVT algorithm to restore the matrix,combines wit the super-resolution spectrum estimation and other techniques to obtain the reconstructed INCM,the desired steering vector and the optimal weight vector.The algorithm improves the efficiency of degree-of-freedom utilization and the performance of the beamformer.