基于压缩感知的信号重建方法及在气枪震源信号处理中的应用

在气枪源探测过程中,由于各种干扰因素的影响,导致部分有效信号缺失或受随机干扰严重,为了重构出连续完整的数据,依据气枪源信号在傅里叶变换域中具有稀疏性的特点,构建了一种基于压缩感知(Compressive Sensing,简称CS)的缺失信号重建方法.首先进行数值模拟,并将该方法与传统的插值方法处理效果进行对比,对重建效...

Signal Reconstruction Method Based on Compressive Sensing and Its Application in Signal Processing of Air-Gun Sources

In air-gun source detection, some effective signals are missing or seriously disturbed by random signals due to the influence of various interference factors. To reconstruct continuous and complete data, a missing signal reconstruction method based on compressive sensing is constructed according to the sparse characteristics of air-gun source signals in a Fourier transform domain. First, a numerical simulation is carried out, and the processing effect of this method is compared with that of the traditional interpolation method. The root mean square error and signal-to-noise ratio analyses of the reconstruction effect are carried out. Results show that the compressive sensing method has a high waveform coincidence, strong amplitude consistency, and clear and continuous phase axis and suppresses noise before and after reconstruction. In conclusion, the reconstruction effect of this method is better than that of the traditional cubic spline interpolation method. The method is applied to practical data, and the results show that the interfered effective signal can be well reconstructed.