基于独立分量分析下的跳频网台分选  

Based on Independent Component Analysis of the Frequency-hopping Station Sorting

作　　者：杨芸丞 孙雪丽 朱念斌 YANG Yuncheng;SUN Xueli;ZHU Nianbin(Naval Aviation University,Yantai 264001;No.61923 Troops of PLA,Beijing 102446)

机构地区：[1]海军航空大学 [2]61923部队

出　　处：《舰船电子工程》2018年第6期41-45,共5页Ship Electronic Engineering

基　　金：国家自然科学基金项目(编号:61179016);国家自然科学基金重大研究计划(编号:91538201)资助;泰山学者工程专项基金项目(编号:ts201511020)

摘　　要：复杂电磁环境条件下,针对目前多跳频信号的网台分选特征参数识别算法时效性不强且算法复杂度高等问题,提出了一种基于Fast ICA的跳频网台分选方法。首先基于独立分量分析思想,建立起参数识别的算法模型;然后利用固定点算法,以负熵最大作为目标函数,完成了对混叠跳频信号的盲源分离。仿真实验表明,在-3d B的信噪比条件下,较非线性PCA算法,分离速度提升45%左右,分选准确度达到95%以上。Complex electromagnetic environment conditions, according to the present more frequency hopping signal feature parameter identification algorithm of network station sorting high timeliness is not strong and the complexity of algorithm, this paper proposes a frequency hopping based on FastlCA net station sorting method. Firstly, based on independent component analysis, the algorithm model of parameter identification is established. Then, using the fixed point algorithm, the negative entropy is the maxi- mum target function, and the blind source separation of the mixed frequency hopping signal is completed. The simulation results show that, under the condition of-3db＇s SNR, the separation speed is increased by 45% and the separation accuracy is over 95%.

关 键 词：跳频 最大负熵 固定点算法 独立分量分析 网台分选 

分 类 号：TN974[电子电信—信号与信息处理]