ANTENNA POSITION OPTIMIZATION BASED ON ADAPTIVE GENETIC ALGORITHM FOR DISTRIBUTED ARRAY RADAR

The detection performance of distributed array radar would be heavily influenced by the inappropriate design of antenna positions. Thus, an antenna position optimization method based on adaptive genetic algorithm is proposed. In the proposed method, the antenna position is directly coded as a chromosome with multiple constraints. And the fitness value of the chromosome is calculated according to the peak side lobe level (PSLL) of the beam pattern. Then, the probabilities of crossover and mutation are adaptively calculated for the chromosome. And the two-point crossover method and one-point mutation method are applied based on the adaptive probabilities. Because of the adaptive probabilities, the proposed method can not only obtain the antenna positons with lower PSLL, but also can get approximate PSLL with other methods by fewer antennas. Based on the simulation with linear coherent aperture radar, the proposed method is verified and the antenna positions with lower PSLL is get compared with conventional methods.