Optimization of the Sparse Array with Enhanced Degrees of Freedom and Low Mutual Coupling

We propose a novel sparse array design method to address the problem of the direction of arrival error caused by the difficulty in achieving synchronous optimization of uniform degrees of freedom and mutual coupling effects in existing sparse arrays. Unlike traditional sparse array design methods, the proposed method is based on an array sparse optimization model, with the optimization goal of improving uniform degrees of freedom and reducing mutual coupling. The Grey Wolf Optimizer with adaptive weights is used to optimize the distribution of array sensors under a given array aperture and sensor quantity, and then the designed array is obtained. Compared with existing sparse arrays, the sparse array derived by the proposed method possesses flexible sensor distribution and maintains a higher uniform degree of freedom while significantly reducing mutual coupling effects. Simulation experiments are conducted, and the results show that the designed sparse array performs better in the direction of arrival estimation, verifying the effectiveness of the design.