Spatial, Temporal, and Spectral Aspects of Far-Field Radar Data

摘要

We develop a linearized imaging theory that combinesthe spatial, temporal, and spectral aspects of scatteredwaves. We consider the case of fixed sensors and a generaldistribution of objects, each undergoing linear motion; thus thetheory deals with imaging distributions in phase space. We derivea model for the data that is appropriate for any waveform, andshow how it specializes to familiar results when the targets arefar from the antennas and narrowband waveforms are used.We use a phase-space imaging formula that can be interpretedin terms of filtered backprojection or matched filtering. For thisimaging approach, we derive the corresponding point-spreadfunction. Special cases of the theory reduce to: a) Range-Doppler imaging, b) Inverse Synthetic Aperture Radar (ISAR)and Spotlight Synthetic Aperture Radar (SAR), c) DiffractionTomography or Ultra-narrowband imaging, and d) Tomographyof Moving Targets.