典型电磁泄漏信号特征提取与统计分析

Feature Extraction and Statistical Analysis of Typical Electromagnetic Leakage Signals

电磁泄漏信号含有许多反映其属性的特征参数。为了充分挖掘信号中的隐藏信息,实现信号识别、分类等多种目标,需要对信号进行特征提取与特征参数统计分析。通过建立时域、频域的特征提取方法和对典型电磁泄漏信号特征参数统计分布的分析,初步验证了特征提取与统计分布可作为电磁信息安全信号识别工作中的一种预处理方法。不仅可以更直观地呈现出电磁特征,也为有效信号的筛选和信号的识别与分类提供了一个具体量化的参考,解决了简单目标不同状态或不同行为的粗分类问题,进而为异常信号检测、设备行为识别等应用提供了有力支撑。

The electromagnetic leakage signal contains many characteristic parameters reflecting its attributes.In order to fully mine the hidden information in the signal and realize multiple targets such as signal identification and classification,it is necessary to carry out feature extraction and feature parameter statistical analysis of the signal.Through the establishment of time domain and frequency domain feature extraction method and the analysis on statistical distribution of characteristic parameters of the typical electromagnetic leakage signal,it is preliminarily verified that feature extraction and statistical distribution can be used as a preprocessing method in the identification of electromagnetic information security signals.It can not only present the electromagnetic characteristics more intuitively,but also provide a specific quantitative reference for the selection of effective signals and the recognition and classification of signals,and solve the problem of rough classification of different states or different behaviors of simple targets,and then provides strong support for applications such as abnormal signal detection and device behavior recognition.