To gain the tradeoff between lower sidelobe and higher power amplifiers efficiency,a transmitting beam shaping scheme with limited amplitude weight values for satellite active phased array antenna is presented. The sc...To gain the tradeoff between lower sidelobe and higher power amplifiers efficiency,a transmitting beam shaping scheme with limited amplitude weight values for satellite active phased array antenna is presented. The scheme is implemented by a dual coding genetic algorithm(GA). Phase and amplitude of array weight vectors for beam shaping are encoded by real coding and finite length binary coding,respectively,which,maintaining accuracy of results,reduces the amplitude dynamic range and improves the efficiency of power amplifiers. The presented algorithm,compared with complex-coded GA,increases the convergence rate due to the search space's decrease. In order to overcome the prematurity and obtain better global optimization or quasi-global optimization,a new dual coding GA based on "species diversity retention" strategy and adaptive crossover and mutation probability are presented.展开更多
基金The project supported by National Natural Science Foundation of China (No. 60572095)Research Foundation for Doctors of ZZULI
文摘To gain the tradeoff between lower sidelobe and higher power amplifiers efficiency,a transmitting beam shaping scheme with limited amplitude weight values for satellite active phased array antenna is presented. The scheme is implemented by a dual coding genetic algorithm(GA). Phase and amplitude of array weight vectors for beam shaping are encoded by real coding and finite length binary coding,respectively,which,maintaining accuracy of results,reduces the amplitude dynamic range and improves the efficiency of power amplifiers. The presented algorithm,compared with complex-coded GA,increases the convergence rate due to the search space's decrease. In order to overcome the prematurity and obtain better global optimization or quasi-global optimization,a new dual coding GA based on "species diversity retention" strategy and adaptive crossover and mutation probability are presented.
