Array antenna with reconfigurable elements can further suppress the peak sidelobe level (PSLL) by selecting reconfigurable element pattern (REP) combination according to the variation of the beam directions. However, the pattern selection for N array elements from K possible REPs is a typical non-deterministic polynomial-hard problem, resulting in the REP selection being intractable even with small N and K. To solve this REP selection problem effectively, this paper proposes an improved genetic algorithm to shrink the REP combinations that contain the suboptimal one. As a result, the proposed algorithm can adaptively select the best REP combination for different scanning beams by searching a relatively minor solution space. The alternating direction multiplier method is used to accelerate the computational speed of optimizing the array excitation. Array antennas with two-type REPs and three-type REPs, respectively, are simulated with high-frequency simulation software (HFSS) to validate the superiority of the proposed algorithm. Comparisons with the existing algorithms show that the proposed algorithm can select a superior REP combination to obtain 1 dB to 3 dB lower PSLL for different scanning beams.
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