基于相移偏移和匹配追踪的探地雷达成像方法

GPR imaging method based on the phase shift migration and the least-square matching pursuits

把非均匀采样快速傅里叶变换(NUFFT)算法引入到探地雷达(GPR)成像的相移偏移算法中,避免了常规相移算法中的插值运算,实现了相移偏移的高精度快速计算;把最小二乘原理引入到匹配追踪(MP)算法中,克服了MP算法中寻找最优原子的耗时过程,并使用解析道和解析子波,实现了GPR信号谱分解的快速计算。然后,综合改进的相移偏移方法与最小二乘匹配追踪算法,提出了一种计算GPR偏移成像结果振幅谱和相位谱的方法,更有效地反映地下媒质的结构特征。模拟资料和实测资料的测试结果表明:相对单纯相移偏移方法,该综合方法能有效压制噪声,极大地改善含噪声资料的成像质量,而且,综合分析幅度谱和相位谱,可以提高识别和圈定目标体的能力。

A ground penetrating radar （GPR） imaging method is proposed based on the combination of the phase shift migration method and the least-square based matching pursuit algorithm （LSMP）, which produces the amplitude spectrum and the phase spectrum of the migrated data. The non-uniform fast Fourier transform （NUFFT） is incorporated into the phase shift migration method to evaluate the in- verse FFT more accurately and more efficiently than the conventional methods, which requires the interpolation of non-uniformly sampled data in wave-number space, before the regular FFT can be applied. The LSMP, in which the least-squares concept is introduced to the matching pursuit algorithm to avoiding the greedy search of the optimal atom in the atom dictionary, is applied to implement efficient- ly the spectral decomposition of the migrated data based on analytic trace and ana- lytic wavelets. The combined method proposed in this paper is tested on numericalsimulated data and field data. The results show that, compared to the phase shift migration, the combined method has an advantage of suppressing random noise and improving the GPR imaging quality greatly, and the detection and localization of GPR objects can be enhanced from low signal to noise ratio data by combing the am- plitude spectrum and the phase spectrum.