基于时频特征的光纤周界入侵振动信号识别与定位

Recognition and Localization of Intrusion Vibration Signal Based on Time-Frequency Characteristics in Optical Fiber Perimeter Security

针对光纤周界安防系统入侵信号的非线性、非平稳性和间歇性等特点,提出了一种时域与频域特征相结合的方法,对光纤周界安防系统入侵振动信号进行识别与定位。采用计算嵌入维数方法,确定信号的最小分帧长度,因而能够较好地保留信号时间序列内在的动力学特性;提出了对入侵振动信号两级判定识别方法,利用短时能量和短时平均过零率特征来判断是否有振动信号产生,依据振动信号各层小波系数的能量分布特点来识别入侵信号,该方法有效地降低了周界安防系统的漏识率和误识率;为提高入侵信号定位的准确性,采用小波域贝叶斯自适应阈值对入侵信号作降噪处理,将重建的信号转换到频率域来确定入侵信号的位置。通过实验验证了所提方法的有效性。

In order to deal with the nonlinearity, non-stationarity and intermittence of intrusive vibration signal in the optical fiber perimeter system, a method combining time and frequency domains characteristics is proposed to distinguish and locate intrusive vibration signal. The minimum frame length is determined by computing embedded dimension to better reserve the dynamic characteristic of the time series signal. The two stages judging and recognizing methods of intrusive vibration signal are proposed. Firstly, short-term energy and zero-crossing measurements are used for determining whether the vibration signal is generated, and then the intrusive signal is recognized according to the characteristic of the energy distribution of each layer＇s wavelet coefficients. This method effectively reduces the efficiencies of recognizing error and loss for optical fiber perimeter system. In order to improve the accuracy of locating intrusive signal, Bayesian adaptive threshold estimation in wavelet domain is applied to reduce the noise of the signal, and the reconstruction signal is finally transformed to frequency domain to find the intrusive point. The experiments result shows that the proposed algorithm is effective.