降低OFDM雷达PAPR的SLM改进算法研究

Improved SLM Algorithm for Reducing PAPR of OFDM Radar

正交频分复用(orthogonal frequency division multiplexing,OFDM)雷达信号具有良好的分辨力和较高的频谱利用率,其中基于混沌二相编码调制的OFDM雷达信号由于具有结构灵活、更优的脉压性能和较强抗干扰能力等优点受到广泛青睐,但是在系统中存在的高峰均比问题使得OFDM雷达在实际应用受到限制。针对各载波不同混沌二相编码序列调制的OFDM雷达信号,提出一种基于混沌粒子群的选择性映射(selective mapping,SLM)算法来降低OFDM雷达信号中的高峰均比问题。实验结果表明:相比于传统SLM算法和基本粒子群SLM算法,基于混沌粒子群的SLM算法在降低OFDM雷达信号的峰均比方面具有更好的效果。

Orthogonal frequency division multiplexing（ OFDM） radar signal has good resolution and high spectral efficiency; and OFDM radar signal based on chaotic binary-phase coded modulation is widely favored due to its flexible structure,better pulse compression performance and strong anti-jamming capability. However,the high peak-to-average power ratio in the system makes the OFDM radar limited in practice. A selective mapping（ SLM） algorithm based on chaotic particle swarm optimization（ CPSO） is proposed to reduce the peak-to-average power ratio for the OFDM radar signals modulated by different chaotic binary-phase coding sequences. The experimental results show that the SLM algorithm based on CPSO has better effect in reducing the peak-to-average power ratio of OFDM radar signal than traditional SLM algorithm and basic particle swarm optimization SLM algorithm.