强震动环境下网络通信信号优化提取仿真研究

摘要

This article proposes an extraction method for communication signal under strong vibration environment based on wavelet theory.Firstly,the research separated initial signal and noise band integrated with the wavelet theory and built matching template of signal after de-noising,then carried out wavelet decomposition for signal waiting for extraction and acquired its protocol feature.Next,the research mapped feature space of the initial signal into a higher space on that basis integrated with SVM theory and built optimal classification face of signal feature in space to make signal sample separate accurately and separating interval maximum.Finally,according to that,the communication signals were extracted under strong vibration environment.Simulation results show that the method has higher extraction precision and can reduce the effect of strong vibration noise on communication effectively.%对于强震动环境下网络通信信号的优化提取,可使微弱信号在强震动的环境下更稳定的进行接收和传送.对通信信号的优化提取需要获取待提取信号的协议特征.传统方法将广义峭度的优化准则引入到强震动环境下对通信信号提取过程中,优化准则获得的协议特征模糊,导致优化效果不理想.提出一种基于小波理论的强震动环境下对通信信号提取方法.上述方法先融合于小波原理将原始信号和噪声频带分开,组建降噪后信号匹配模板,将待提取信号进行小波分解,获取待提取信号的协议特征,在此基础上融合于SVM理论将原始信号特征空间映射到一个高维空间,在空间中建立信号特征的最优分类面,使信号样本正确的分离,且分离的间隔最大,以此为依据在强震动环境下对通信信号提取.实验结果表明,所提方法信号提取精确度高,能有效地降低强震动噪声对通信造成的影响.