A Multi-Objective Optimization Subarray Partition Method Based On Particle Swarm Optimization
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摘要: 为了降低硬件成本和系统的复杂度,子阵划分对于大型的相控阵雷达来说是必要的。传统的子阵划分方法主要针对信号处理的单一性能指标优化。针对多项指标优化的问题,本文提出了一种基于粒子群算法的子阵划分结构优化算法,相对于传统的方法能够同时优化多项性能指标,提高信号处理的性能。通过对线性阵列的划分做仿真,展示了粒子群算法对子阵级波束形成多项性能指标的提高。Abstract: In order to debase hardware cost and system complexity, subarray partition is necessary for large phased array antenna. Traditional subarray partition methods are mainly aimed at the single performance optimization of signal processing. In this paper, a subarray structure optimization algorithm based on particle swarm optimization (PSO) is proposed, which can optimize the multiple performances of the signal processing and improve it compared with the traditional methods. Through the simulation of the division of the linear array, the paper demonstrates that particle swarm optimization (PSO) algorithm is proposed to improve the performances of the subarray beamforming.
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