RADAR CLASSIFICATION OF LANDMINES BY TIME-FREQUENCY ANALYSIS

摘要

A flying platform illuminates a land mine field with mixtures of various landmines (I.e., buried, on the surface, plastic or metallic) and some "confusers", with an ultra-wideband (UWB) radar. The polarimetric echoes returned by the mine field are mapped into an overall synthetic aperture radar (SAR) image, which is then analyzed pixel-by-pixel by modern time-frequency (t-f) techniques. The t-f analysis of any echo from any of the individual scatterers in the mine field can be performed using a number of t-f distributions, which in turn generate two-dimensional plots of each such scatterer in t-f space. These plots are richer in information than those in the original SAR image, and they offer a larger variety of clues useful for the discrimination of each type of mine from the others or from the confusers. Several t-f distributions are employed in the study, and it is found that some are better than others for the present purpose of target detection and classification. From the images obtained we can conclude that the Pseudo-Wigner-Ville and the Choi-Williams distributions provide the best discrimination results. It is also found that the larger mines such as those denoted here as of "type-1" are the easiest to identify. Using the above-mentioned distributions it follows that the distinction between actual mines and clutter objects (or "confusers") becomes clearer, particularly when the latter objects are metallic. Numerous images generated in this study confirm the above conclusions.