Compressive sensing introduces a new paradigm in RADAR image formation. This approach to image formation supports new concepts for collection of RADAR imagery. The theoretical framework being developed at MTRI allows us to define optimal collection strategies for imaging from networks of RADARs.
General theoretical developments in compressive sensing with particular focus on distributed RADAR sensing/imaging. Incorporates
The figures above result from image formation processing of synthetic RADAR returns from antennas illuminating six point targets. Five antennas form a sparse array with randomly chosen azimuths spanning 18.
Nikola Subotic, Ph.D.
Co-Director
734.913-6859
nikola.subotic@mtu.edu
Joseph Burns, Ph.D.
Senior Research Scientist
734.913.6857
joseph.burns@mtu.edu
Many environments, including cities, have sparse representations in collected RADAR signals permitting good representation with wise selection of parameters. Below is a collection of radar signals of a building.