Sidelobe minimization of uniform linear array by position- and amplitude-only control using WDO technique

Abstract

This paper describes efficient optimization wind-driven optimization (WDO) technique for pattern synthesis of uniform linear array (ULA) having maximum sidelobe level (SLL) suppression, constrained on DRR, beam width and null control by controlling the amplitude-only and position-only of array element. The single, multiple (double and triple), and broad nulls are placed in the direction of maximum interference while receiving signal from the desired direction. The WDO is a new nature-inspired evolutionary algorithm derived from to the point movement of the air parcel in the earth’s atmosphere. It uses a new learning strategy to update the velocity and position of air packets based on their present pressure values to accelerate the convergence. The six examples are considered, and the results are compared with those obtained by others such as PSO, comprehensive learning PSO, differential evolution (DE), bacterial foraging optimization (BFO), plant growth simulation algorithm (PGSA), and BEES algorithm. The simulation study demonstrates that improves performance of WDO algorithm than twelve reported algorithms particularly in terms of maximum SLL suppression, beam width control, null control, and convergence rate.