Fast Angular Resolution Enhancement for Two-Dimensional Array Radar by 2D Low-Rank Truncated Singular Value Decomposition

Ground-based two-dimensional (2D) array radar suffers from low angular resolution, including azimuth and pitch directions because of the limited size of antenna aperture. In this paper, to improve the two-dimensional angular resolution for a ground-based 2D array radar, a 2D low-rank Truncated Singular Value Decomposition (2D-LRTSVD) superresolution algorithm is proposed by transforming the 2D deconvolution problem into several low-rank inversion problem. First, the traditional 2D convolution signal model is transformed as a low-dimensional signal model by dividing the Kronecker product matrix into several low-dimensional steering matrices. Second, a 2D-LRTSVD method is proposed by compressing the data dimensions of the low-rank steering matrices. Based on the proposed method, the operational complexity can be reduced by avoiding direct high-dimensional matrix inversion. Finally, the 2D angular resolution of array radar can be enhanced without performance loss in a low computational complexity. Simulations are carried out to verify the proposed method.