Virtual Array Design via Hole-Free Sparse Array With Reduced Mutual Coupling Effect

Sparse linear arrays (SLAs) are becoming increasingly popular due to their superior performance in achieving higher degrees of freedom (DOFs) compared to uniform linear arrays. However, most SLA design methods are inflexible for different DOFs; therefore, they are not well suited to addressing the problem of designing the desired virtual array configuration. In this article, we propose two methods for designing SLAs based on the coordinate descent algorithm with a maximum block improvement selection rule. These methods achieve the desired DOF and minimize the number of required sensors while considering the mutual coupling effects between array elements. The first method focuses on optimizing the array for minimal sensor usage, while the second method further enhances performance by reducing mutual coupling. In addition, we address the virtual array design problem in multiple-input multiple-output radar systems. The proposed methods are applied to achieve desired configurations in both 2-D planes and filled linear arrays. The results confirm that the proposed methods offer improved suppression of mutual coupling and leakage when compared to state-of-the-art approaches. Furthermore, the simulation results demonstrate that the desired virtual arrays can be reliably constructed in various scenarios.