volume | PIER Journals

Abstract

In this paper, Enhanced Practical Swarm Optimization (EPSO) algorithm is proposed to be applied to pattern synthesis of linear arrays. Updating formulas of global best particle position and velocity are modified to improve the convergence accuracy of classical Practical Swarm Optimization. The developed EPSO is tested and compared with a standard benchmark to be validated as an efficient optimization tool for beamforming applications. Different numerical examples are presented to illustrate the capability of EPSO for pattern synthesis with a prescribed wide nulls locations and depths. Collective multiple deep nulls approach and direct weights perturbations approach are considered to obtain adaptive wide null steering subject to peak side lobe level and minimum main beam width constraints. Starting from initial chebyshev pattern, single or multiple wide nulls are achieved by optimum perturbations of elements current amplitude or complex weights to have either symmetric or asymmetric nulls about the main beam. Proper formation of the cost function is presented for all case studies as a key factor to include the pattern constraints in the optimization process.

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Dr. Mohab Abd-Alhameed Mangoud

Dr. H. M. Elragal