New approach in the problem of subsurface objects detection using remote sensing technique

This study investigates the problem of detecting buried objects. The work was directed at the processing of synthetic aperture radar (SAR) images. In order to model the scattering of a group of objects embedded in a lossy medium under a rough boundary, we applied the method of Green’s functions and extended the Kirchhoff approximation for the case of composed systems. With this model, we studied the radar response in the form of intensity and correlation imaging function and found that the application of the correlation imaging function significantly improves a ratio between the scattered signal from buried objects and the scattering from a rough boundary. As a result, the detection of buried objects can be realized on larger lengths and with stronger roughness of boundary. To reduce the influence of wave decaying in the lossy medium, we introduced a weighting function. Comparison of radar return with and without this weighting function proved the effectiveness of our method. This allowed us to obtain the object’s image with a much smaller level of signal, and processing the scattered signal with additional weighting function enabled to estimate the depth at which the objects are buried under the boundary.