Improved RF Subsurface Imaging Under Complex Terrain by Synergistic Use of Radar and LiDAR

The conventional Ground Penetrating Radar (GPR) usually requires the system to be in direct contact with the ground surface, which becomes challenging to be utilized for subsurface imaging of undulating and risk-prone terrain. The subsurface image of the terrain in this kind of situation is typically obtained using the synthetic aperture radar (SAR) algorithms by assuming a homogenous half-space with a planar interface. However, such types of complex terrains are non-planar in most situations. In this work, a novel LiDAR assisted RF imaging methodology is proposed to retrieve the subsurface image of complex terrains by considering their non-planarity and utilizing a non-contacting measurement procedure. The effectiveness of this approach is demonstrated through laboratory experiments carried out using an automated subsurface imaging testbed with a monostatic radar and a co-located LiDAR sensor. The conventional imaging algorithm is successfully modified to integrate both radar and LiDAR data to compensate for the terrain induced errors. Comparative study of results from the modified and the conventional imaging algorithm reveals improvement in reconstruction of the target’s geometry, its reflection amplitude as well as accurate localization. The proposed scheme can potentially be utilized for various real world applications such as the rockmass inspection in underground mines.