基于小波能谱分析的岩溶区探地雷达目标识别

Objects recognition of ground penetrating radar in karst regions using wavelet energy spectrum analysis

目前常用的根据记录波形的频率、振幅等特征进行岩溶区探地雷达目标识别的方式具有一定的局限性,为此提出了利用小波能量谱特征进行识别的新方法.通过对岩溶区典型样本进行分析,构造雷达信号各频率成分在各尺度上的能量特征向量,得到样本模型的能量谱,将待识别目标体的能量谱特征与之比对,数据分析和实际验证表明,小波特征能量谱具有直观地显示目标信号不同特征的优点,能有效地对岩溶区探地雷达剖面目标体进行识别.

The frequency and amplitude characteristics derived from the Ground Penetrating Radar（GPR） data have been widely applied to object recognition in the karst area, but still meet some limitations. Here we present a new method using wavelet energy spectrum analysis. First we analyze the GPR signals of typical samples in the karst area and obtain their wavelet energy spectrum, which consist of the energy eigenvectors at different scales and frequency bands. Then the object recognition is achieved by comparing the characteristic energy spectrum with those of studied object. Both the data analysis and experiments demonstrate that the wavelet energy spectrum can directly show characteristics of object signals, which is very effective for the object recognition in the karst region from the GPR survey.