An evolutionary method based on backtracking search optimization algorithm (BSA) is proposed for linear antenna array pattern\nsynthesis with prescribed nulls at interference directions. Pattern nulling is obtained by controlling only the amplitude, position, and\nphase of the antenna array elements. BSA is an innovative metaheuristic technique based on an iterative process. Various numerical\nexamples of linear array patterns with the prescribed single, multiple, and wide nulls are given to illustrate the performance and\nflexibility of BSA. The results obtained by BSA are compared with the results of the following seventeen algorithms: particle swarm\noptimization (PSO), genetic algorithm (GA), modified touring ant colony algorithm (MTACO), quadratic programming method\n(QPM), bacterial foraging algorithm (BFA), bees algorithm (BA), clonal selection algorithm (CLONALG), plant growth simulation\nalgorithm (PGSA), tabu search algorithm (TSA),memetic algorithm (MA), non dominated sorting GA-2 (NSGA-2),multiobjective\ndifferential evolution (MODE), decomposition with differential evolution (MOEA/D-DE), comprehensive learning PSO (CLPSO),\nharmony search algorithm (HSA), seeker optimization algorithm (SOA), andmean variance mapping optimization (MVMO). The\nsimulation results show that the linear antenna array synthesis using BSA provides low side-lobe levels and deep null levels.
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