基于改进遗传算法的相控阵雷达最优子阵划分
Optimal Subarray Partition of Phased Array Radar Based on Improved Genetic Algorithm
摘要:
相控阵雷达通常采用子阵结构；子阵结构对系统性能有显著影响，最优子阵划分是具有重要应用意义的课题。本文利用遗传算法对子阵进行优化，以得到最优的旁瓣性能。给出遗传算法的目标函数及子阵结构的编解码方法。提出基于自适应交叉算子的改进遗传算法，使遗传算法具有自适应交叉组合的特点，使子代种群更为优化，较大提高了收敛速度和运算效率。仿真结果证明了所提出方法的有效性。
Abstract:
Subarray structure is usually adopted by phased array radar, and has a significant impact on the performance of the system. The optimal subarray division is the important task with great practical significance. The genetic algorithm was used to optimize the subarray to get optimal sidelobe performance. The objective function of the genetic algorithm and the encoding and decoding method of the subarray structure were given. The improved genetic algorithm based on adaptive crossover operator was proposed, which has the characteristics of adaptive cross combination and more optimized offspring population, and so the convergence speed and operational efficiency were greatly improved. Simulation results show the effectiveness of the proposed method.
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