Antenna Placement in Compressive Sensing Radar Using Binary Optimization

Compressive sensing has allowed for the improve-ment of angular resolution in radar technology, which involves two aspects: sparse signal recovery and measurement matrix design. Assuming a sparse target scene, compressive sensing radar depends solely on the design of the measurement matrix to possess certain properties, such as satisfying the restricted isometry property (RIP) and low coherence. The design of the measurement matrix depends on the location of the antennas. In this work, we consider the antenna placement problem in compressive sensing radar. The problem is interpreted as a binary program, where we propose to solve it directly using a heuristic binary optimization algorithm. The proposed binary differen-tial evolution (BDE) algorithm is able to navigate the search space with relatively high diversity while still refining promising candidates. Results illustrate the superiority of approaching the problem directly using BDE rather than resorting to relaxation approaches in the literature.