We consider migration based synthetic aperture radar (SAR) imaging
of surfaced or shallowly buried objects using both down-looking and
forward-looking ground penetrating radar (GPR). The well-known
migration approaches devised to image the interior of the earth are
based on wave equations and have been widely and successfully used
in seismic signal processing for oil exploration for decades. They
have exhibited great potentials and convenience to image the
underground objects buried in complicated propagation medium.
Compared to the ray-tracing based SAR imaging methods, the migration
based SAR imaging approaches are more suited for the imaging of the
underground objects due to their simple and direct treatment of the
oblique incidence at the air-ground interface and the propagation
velocity variation in the soil. In this paper, we apply the
phase-shift migration approach to both the constant-offset and the
common-shot experimental data collected by the PSI (Planning Systems
Inc.) GPR systems. We will address the spatial aliasing problems
related to the application of migration to the GPR data and the spatial zero-padding approach to circumvent the problem successfully.
Planning Systems Incorporated (PSI) has developed a promising Ground Penetrating Synthetic Aperture Radar (GPSAR) system to detect buried landmines. GPSAR can be used to generate three-dimensional (3-D) mine images. It has been shown that the SAR processing in the PSI GPSAR system can greatly improve the image quality and hence the mine (especially plastic mine) detection performance. In this paper, two special issues on SAR processing for the PSI system are addressed. One issue is the analysis of the effect of the underground electromagnetic (EM) wave propagation velocity uncertainty on SAR processing and the other is channel mismatch on SAR processing. Since the EM wave propagation velocity in the soil depends on many factors and changes from one location to another, velocity uncertainty is inevitable. However, we have found that the PSI GPSAR system is very robust against the velocity uncertainty. More specifically, velocity uncertainty does not defocus the image but only scales the image along the depth dimension, and hence will not affect the mine detection performance. Another issue is how to select a good SAR processing scheme for the PSI system. Because the radar footprint is 2-D (along-track and cross-track dimensions), 2-D SAR processing may be used. However, the effectiveness of the 2-D SAR processing depends on the coherence of the radar antenna system. Moreover, the computational expense of the 2-D SAR processing is much higher than that of the 1-D SAR processing (along-track dimension only). We have found that due to the channel mismatch of the PSI system, the 2-D SAR processing does not greatly improve the quality of the SAR images when compared with 1-D SAR processing. Hence, without proper antenna calibration, the computationally more efficient 1-D SAR processing may be preferred for the PSI system.
For downward looking GPR landmine detection systems, the return from the ground surface, i.e., the ground bounce, often surpasses the actual mine return and makes it almost impossible to detect the landmines, especially the buried plastic landmines. The ground bounce is difficult to remove due to the roughness of the ground surface and/or the changing soil conditions. In this paper, a robust and efficient ground bounce removal algorithm, referred to as ASaS (Adaptive Shift and Scale), is presented. ASaS takes into account the variations of the ground bounce by adaptively selecting a reference ground bounce. The shifted and scaled version of the reference ground bounce is used as the estimate of the ground bounce in the current scan. Two adaptive reference selection schemes for ASaS are given and compared with each other. Experimental results based on the data collected by the PSI GPSAR system are used to demonstrate the effectiveness of the adaptive schemes.