Compressed sensing is a signal processing paradigm enabling the acquisition and successful reconstruction of a sparse signal from a reduced set of measurements, potentially in violation of the Nyquist sampling criterion. In this paper the results of preliminary investigations into Compressed Sensing applied to the acquisition of wide bandwidth millimeterwave compact radar range data are presented. Primary motivations for application of Compressed Sensing to compact radar range acquisition and imaging include increasing data acquisition speed as well as reducing required data storage. In this work only signal reduction in the frequency domain is examined. Compressed Sensing fully-polarimetric compact range data acquisition and imaging for both a simple canonical target (cylinder) and a complex target (Slicy) are presented as radar cross section (RCS) measurements and interferometric inverse synthetic aperture radar (IFISAR) images. Correlations of compact range data provide a measure of error between the reconstructed and complete data sets as a function of target complexity and sub-sampling rate.
Three-dimensional radar imaging is becoming increasingly important in modern warfare systems, leading to an increased need for deeper understanding of the 3D scattering behavior of targets as simple as a cylinder, to as complex as a main battle tank or air defense unit. Fully polarimetric, three dimensional radar signature data have been collected using 1/16th scale models of tactical targets in several indoor compact radar ranges, corresponding to data from S-band to W-band. ISAR image pairs, collected at slightly different elevations, were interferometrically processed into 3D imagery. The data collection, analysis, and 3D visualization methods are presented. Additionally, the results of mathematical 3D correlation are described. A detailed analysis of both measured and predicted 3D radar data on the UMass Lowell nominal rocket simulator target will be presented.