摘要
在实际应用场合中,相控阵雷达的阵列天线所包含的阵元数往往很多,使得对信号处理机的硬件结构和运算处理能力的要求非常高,针对该情况,提出了基于粒子群算法的子阵合成方法。由于均匀无重叠子阵合成存在的测角模糊,以及均匀重叠划分带来的硬件设备量的增加,考虑采用非均匀子阵合成结构。该方法以角度估计的克拉美罗界为适应度函数,通过粒子群算法进行子阵优化,避免了遗传算法的选择、交叉和变异,操作简单,收敛速度快。计算机仿真验证了该方法的有效性和可行性。
In practical applications, since tremendous data are usually involved in phased array radar, the requirement of hardware construction and processing power of signal processor is extremely high. In this paper, an approach to synthesis of subarray based on particle swarm optimization （PSO） is presented. The non-uniform subarray is utilized due to the angle ambiguity existing in the uniform non-overlapping configuration and the increasing devices required in the uniform-overlapping one. This method uses the Cramer-Rao bound of the angle estimation as fitness function and the subarray is optimized through PSO. Compared with genetic algorithm （GA）, the PSO algorithm can not only avoid selection, crossover and mutation but also be operated simply and converge rapidly. Simulations show the validity and feasibility of the method.
出处
《计算机时代》
2013年第7期3-7,共5页
Computer Era
基金
浙江省自然科学基金青年基金项目(LQ12F01002)
关键词
阵列天线
粒子群算法
子阵合成
克拉美罗界
适应度函数
array antenna
particle swarm optimization（PSO）
synthesis of subarray
Cramer-Rao bound（CRB）
fitness function
