Steering invariant beam optimization method for uniform circular array based on compressed sensing

For the existing steering invariant beamforming algorithm, after the number of elements is determined, the main lobe and side lobe levels of the beam cannot be further improved. Based on the existing steering invariant beamforming methods of a uniform circular array and through introducing Compressed Sensing theory (Compressed Sensing, CS), this paper proposes a method that can further improve the level of the main and side lobes of the beam. This method uses compressed sensing theory to compress the signal and sparsely reconstruct the signal, and uses the second-order cone programming method in the convex optimization to perform steering invariant beamforming on the recovered signal, which can increase the array aperture without increasing the actual number of elements, and can obtain a beam pattern with a lower side lobe level and a narrower main lobe width. Simulation results show that this method improves the performance of the beamformer to a certain extent, and it has certain theoretical and practical significance in array signal processing.