Signal processing aspects of polarimetric random noise radar data for shallow subsurface imaging

A novel polarimetric random noise radar system has been developed by the University of Nebraska for shallow subsurface probing applications. The radar system has been fabricated and tested, and its initial performance has been found to be quite satisfactory in detecting and locating buried objects. The system produces images of the co-polarized amplitude, cross-polarized amplitude, depolarization ratio, and polarization phase difference of the radar reflected signal as the antennas are scanned over the surface below which the objects are buried. Various signal processing algorithms are being explored to enhance target detection and clutter suppression. Since the radar system provides polarization phase differences between the orthogonal receive channels, algorithms based on Stokes matrix processing are being explored to detect and identify specific targets. One of the main advantages of Stokes matrix processing is in detecting long and slender cylindrical targets, which are not clearly detected in the conventional images. Furthermore, the optimal use of thresholding and smoothing operations to reduce and eliminate clutter is being examined. Examples of the pre-processed and post-processed images are presented