SASA: Super-Resolution and Ambiguity-Free Sparse Array Geometry Optimization With Aperture Size Constraints for MIMO Radar

To improve the performance of multiple-input–multiple-output (MIMO) radar, various sparse arrays have been used. However, the angular resolution of existing nonuniform arrays optimized by either combinatorial algorithms or heuristic ones is limited by the Rayleigh criterion, which is strictly related to the aperture size. Based on the angular ambiguity function (AAF) analysis, two new models are established in this work for directly optimizing the sidelobe level (SLL) or the main lobe width (MLW) with the constraints of aperture size and element spacing. The aforementioned designs result in non-convex and nonlinear optimization problems, and solutions are derived via the alternating direction multiplier method (ADMM). Furthermore, considering a parametric tradeoff between SLL and MLW, a hybrid algorithm is proposed to search for the SLL-MLW Pareto front boundary. Finally, simulations are provided to demonstrate the high angular resolution and ambiguity-free properties of the optimized sparse arrays.