小波变换实现混沌雷达高精度泄漏检测研究

A Study on High Precision Leak Detection of Chaotic Radar by Wavelet Transform

利用超宽带电混沌信号的强抗干扰性和随机性，通过分析超宽带混沌信号和经管道反射后雷达回波信号的互相关函数以及峰值信噪比，对管道泄漏点进行定位。在接收端，通过对雷达回波信号的小波阈值去噪和数据分析，探究小波基sym4在3、4、5层小波分解之后的去噪效果，有效提高泄漏的检测精度。结果表明：小波基sym4，在加入5dB高斯白噪声情况下，互相关系数方法中，采用4层分解的硬阀值法可以取得最佳去噪效果；小波基sym4，在加入5dB高斯白噪声情况下，峰值比信噪比方法中，采用5层分解的硬阈值法可以取得最佳去噪效果，从而实现高精度泄漏检测。

A new method of pipeline leak detection and location is proposed. The cross-correlation function and the peak signal-tonoise ratio of the radar echo signal of the UWB signal chaotic signal is studied by using its strong anti-jamming and randomness. At the receiver, the wavelet threshold denoising and data analysis of the radar echo signal are used to investigate the denoising effect of the wavelet base sym4 in the 3, 4, 5 layer wavelet decomposition, and efficiently increase the detection precision of the pipeline leak. The results show that the wavelet base sym4 can obtain the best denoising effect by using the hard threshold method of 4-layer decomposition in the case of 5 dB Gaussian white noise. In the case of adding 5 dB Gaussian white noise, the peak signal to noise ratio method, the use of 5-layer decomposition of the hard threshold method can achieve the best denoising effect, in order to achieve higher accuracy.