移动网络通信入侵干扰信号优化检测仿真
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摘要
对移动网络通信入侵干扰信号的优化检测,能够有效的对无线网络的入侵信号进行快速截获,保证网络的安全性。对通信入侵干扰信号的检测,需要设计熵特征检测器,给出通信入侵干扰信号检测门限,完成对网络入侵信号的优化检测。传统方法先对干扰噪声进行估计,对通信入侵干扰信号特征进行提取,但忽略了给出通信入侵干扰信号检测门限,导致检测精度偏低。提出基于熵特征的移动网络下通信入侵干扰信号优化检测方法。上述方法先基于概率统计方法提取干扰信号频谱特征,计算移动网络下所有幅值出现的总概率,利用经验模态分解方法分离出通信入侵干扰信号谐波分量,给出干扰谐波分量与目标回波在时频域上能量分布特征差异,设计熵特征检测器,给出移动网络下通信入侵干扰信号检测门限,完成对移动网络下通信入侵干扰信号优化检测。实验结果表明,所提方法检测精度高,可以有效地消除移动网络下通信入侵干扰信号。
This research puts forward a method for optimization detection of interference signal of communication intrusion in mobile network. Spectrum feature of interference signal based on probabilistic method was extracted and total probability of all amplitude emerging in the mobile network was calculated,then experiential empirical mode decomposition was used to isolate harmonic component of the interference signal and characteristic difference of energy distribution in time-frequency domain of the harmonic component and target echo was provided. The detector of entropy feature was designed and the threshold of detection of interference signal was provided. Experimental results show that the method has higher detection precision and can eliminate the interference signal effectively.
This research puts forward a method for optimization detection of interference signal of communication intrusion in mobile network. Spectrum feature of interference signal based on probabilistic method was extracted and total probability of all amplitude emerging in the mobile network was calculated,then experiential empirical mode decomposition was used to isolate harmonic component of the interference signal and characteristic difference of energy distribution in time-frequency domain of the harmonic component and target echo was provided. The detector of entropy feature was designed and the threshold of detection of interference signal was provided. Experimental results show that the method has higher detection precision and can eliminate the interference signal effectively.
引文
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[2]古培,王斌.基于二次灰度形态学滤波的跳频信号盲检测[J].信息工程大学学报,2015,16(1):79-83.
[3]睢丹,黄永灿.改进网络入侵信号监控系统的设计与应用[J].科技创新导报,2016,13(2):66-67.
[4]范平志,等.高移动性宽带无线通信网络重点理论基础研究2012年度报告[J].科技创新导报,2016,(11):170-171.
[5]郭晓陶,等.基于卷积盲分离的强干扰下通信信号分离算法[J].北京航空航天大学学报,2016,42(6):1295-1302.
[6]段瑞杰,李永贵,惠显杨.短波无线接入网抗干扰需求分析[J].通信技术,2015,48(7):818-824.
[7]陈利军,郭红艳.基于粒子滤波的网络入侵相频特征提取算法[J].科技通报,2016,32(3):101-104.
[8]贾蓓,李敬华,肖飞.基于复杂电磁环境的信号检测模型构建分析[J].信息技术与信息化,2015,7(9):165-166.
[9]曹可劲,等.基于信噪比测量的欺骗干扰检测方法[J].计算机测量与控制,2016,24(4):29-32.
[10]张红斌.物联网络中对入侵信号优化预警仿真研究[J].计算机仿真,2016,33(11):333-336.