Robust Hybrid Algorithm of PSO and SOCP for Grating Lobe Suppression and against Array Manifold Mismatch

Abstract

Based on Particle Swarm Optimization (PSO)and Second-Order Cone Programming (SOCP) algorithm, this paper proposes a hybrid optimization method to suppress the grating lobes of sparse arrays and improve the robustness of array layout. With the peak side-lobe level (PSLL) as the objective function, the paper adopts the particle swarm optimization as a global optimization algorithm to optimize the elements' positions, the convex optimization as a local optimization algorithm to optimize the elements' weights. The effectiveness of the grating lobes suppression (as low as -32.13 dB) by this method is illustrated through its application to the sparse linear array when the actual steering vector is known. To enhance the robustness of the optimized array, a rebuilt robust convex optimization model is adopted in the optimization of both array excitations and layout. When the array manifold mismatch error is 1 cm, the PSLL by the robust algorithm can be compressed to -27 dB, compared to that of -24 dB by the ordinary optimization. Results of a set of representative numerical experiments show that the algorithm proposed in this paper can obtain a more robust array layout and matched elements' weight coefficients to avoid the huge degradation of the array pattern performance in the presence of array manifold mismatch errors. The good performance of pattern synthesis demonstrates the effectiveness of the proposed robust algorithm.

Interference suppression for satellite communications in EHF band based on aperiodic multistage arrays

“…In [9], a movable grid covering structure was proposed to suppress grating lobes. The aperiodic multistage array can also effectively suppress the grating lobe while increasing the array element spacing [10,11], thereby improving the spatial resolution of the beam and solving the anti-jamming problem for satellite communications in the EHF band. The method of optimizing the distribution of sub-arrays based on particle swarm optimization was proposed in [12].…”