基于谱再生逆分析的信号细微特征提取  

Fine Feature Extraction Based on Reverse Analysis of Spectral Regrowth

作　　者：陈健[1] 段田东[1] 徐文艳[1] 吴素琴[1] 

机构地区：[1]解放军信息工程大学信息系统工程学院,河南郑州450001

出　　处：《信号处理》2016年第3期349-354,共6页Journal of Signal Processing

基　　金：国家科技重大专项资助项目(2011ZX03003-003-02)

摘　　要：为解决无线复杂电磁环境下同型号通信电台的个体识别问题,研究谱再生逆分析的细微特征提取方法并改进。首先分析输入信号通过非线性功放后的谱再生现象,然后对其进行逆分析,以功率谱分段拟合的方法提取功放非线性参数作为各电台特征,并对特征提取步骤进行了改进使算法更适用于同型号电台的个体识别。为验证算法有效性,使用SVM分类器对特征进行模式训练和识别,仿真结果表明,算法在高斯信道模型和Watterson短波好信道模型下对同型号电台有较好的识别效果。In order to identify same-model transmitters in complex wireless environment,this paper researches the fine-feature-extraction method making reverse analysis of spectral regrowth and makes a modification. First,we analyzed spectral regrowth of input signal going through power amplifier. Then we extracted nonlinear parameter as the feature of each power amplifier by power fitting of PSD in selected frequency bands. A modified extraction method was presented in this part. At last,the support vector machine is used in training and classifying. Simulation shows that the method performs well identifying same-model transmitters in Gaussian channel as well as good HF Watterson channel.

关 键 词：细微特征 特征识别 功率放大器 谱再生 

分 类 号：TN911.7[电子电信—通信与信息系统]