基于改进遗传算法和SinChirplet原子的调频
雷达信号稀疏分解

doi:10.16183/j.cnki.jsjtu.2017.09.016

摘要/Abstract

摘要： 为构建合适的时频原子库和信号分解算法，提出一种基于改进遗传算法和SinChirplet原子的调频雷达信号稀疏分解算法.这种新的SinChirplet原子在Chirplet原子的基础上增加正弦调频因子，改善原子时频曲线的弯曲性能，使原子对非线性调频信号具有较强的匹配性能.然后基于原子的匹配特性，改进遗传算法中初始原子种群产生机制，提高了最佳原子搜索速度.理论分析和仿真结果表明，基于改进遗传算法的信号稀疏分解效率高于传统遗传算法和匹配追踪算法.相比现有的3种典型时频原子，SinChirplet原子的匹配性能良好，可以更有效地分解调频雷达信号及其混合信号.

关键词: , 时频原子, 信号分解, 改进遗传算法, 调频信号, 稀疏表示, 电子干扰

Abstract: In order to improve the performance of sparse decomposition for radar signals, a signal sparse decomposition algorithm(SDA) based on a novel SinChirplet atomic dictionary and an advanced genetic algorithm(GA) is proposed. Firstly, a sinusoidal frequency modulating factor is added into Chirplet atom so that the curvature performance of the atom timefrequency curve can be improved. Therefore SinChirplet atom has good matching performance for nonlinear frequency modulation signals. Secondly, based on the matching characteristic of SinChirplet atom, the generation of atom initialization population in GA is improved so that the bestatom searching speed can be raised. The theoretical analysis and the simulation results show that the decomposition efficiency of advanced GA is higher than that of GA and matching pursuit(MP) algorithm. Meanwhile, the matching performance and the decomposition efficiency of SinChirplet atom are better than those of other three traditional timefrequency atoms.

Key words: timefrequency atom, signal decomposition, advanced genetic algorithm, frequency modulation signal, sparse representation, electronic jamming

中图分类号:

TN 97

王星，周一鹏，田元荣，陈游，周东青，贺继渊. 基于改进遗传算法和SinChirplet原子的调频
雷达信号稀疏分解[J]. 上海交通大学学报（自然版）, 2017, 51(9): 1124-1130.

WANG Xing,ZHOU Yipeng,TIAN Yuanrong,CHEN You,ZHOU Dongqing,HE Jiyuan. Sparse Decomposition for Frequency Modulation Radar Signal Based on
Advanced Genetic Algorithm and SinChirplet Atom[J]. Journal of Shanghai Jiaotong University, 2017, 51(9): 1124-1130.

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