IMAGING OF OBJECTS FROM RF RADAR RETURNS

This research topic focuses on the design of algorithms to exploit wideband standoff radar data so as to effectively see through walls in order to detect and characterize objects of interest within a building. The hypothesis is that people and objects of interest will exhibit characteristic signatures that allow you to, for example, discern human pose, detect the presence of carried weapons, and detect static weapons caches. In general, these characteristic signatures will be contaminated by through-wall dispersive transmission effects as well as reflective phenomena such as near-field coupling, multipath, and edge/corner diffraction within the building. SET Corp has teamed with The Ohio State University ElectroScience Lab to identify characteristic temporal, polarimetric, and spatial/spectral features and to recover them from the complex EM environment through the use of adapted in situ wall propagation models. We design classifiers that process the recovered characteristic features to provide situation awareness within the room.