压缩感知理论在探地雷达三维成像中的应用

Research on Compressive Sensing Based 3D Imaging Method Applied to Ground Penetrating Radar

该文基于探地雷达成像目标空间的稀疏特性,提出了探地雷达中的随机孔径压缩感知3维成像方法,该方法在单道数据获取中应用压缩感知减少采集数据量的同时,在x-y测量平面上随机抽取部分孔径位置进行测量,以少量的测量孔径和测量数据获得重建目标空间的足够信息,同时该文研究了噪声以及测量矩阵对算法性能的影响。结果表明,随机孔径压缩感知成像算法比传统后向投影算法所需数据量少,成像效果好,目标旁瓣小,对噪声的鲁棒性更好。

Considering the sparse structure of actual target space in GPR application, a novel 3D imaging method based on random aperture compressive sensing is proposed in this paper, which capable of reconstructing the target space from a few compressive sensing data obtained by random aperture measurements, and the imaging performance versus noise level and the effects of different measurement matrices are analyzed. The computer shnulation results indicate that the proposed algorithm allow much fewer data, much shorter measurement time. And due to it is fully utilization of the sparse structure of interested target space, the method show much more robust and sparse image than time-domain standard back-projection method.