Paper
15 April 2008 Imaging that exploits spatial, temporal, and spectral aspects of far-field radar data
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Abstract
We develop a linearized imaging theory that combines the spatial, temporal, and spectral aspects of scattered waves. We consider the case of fixed sensors and a general distribution of objects, each undergoing linear motion; thus the theory deals with imaging distributions in phase space. We derive a model for the data that is appropriate for any waveform, and show how it specializes to familiar results when the targets are far from the antennas and narrowband waveforms are used. We develop a phase-space imaging formula that can be interpreted in terms of filtered backprojection or matched filtering. For this imaging approach, we derive the corresponding point-spread function. We show that special cases of the theory reduce to: a) Range-Doppler imaging, b) Inverse Synthetic Aperture Radar (isar), c) Spotlight Synthetic Aperture Radar (sar), d) Diffraction Tomography, and e) Tomography of Moving Targets. We also show that the theory gives a new SAR imaging algorithm for waveforms with arbitrary ridge-like ambiguity functions.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Margaret Cheney and Brett Borden "Imaging that exploits spatial, temporal, and spectral aspects of far-field radar data", Proc. SPIE 6970, Algorithms for Synthetic Aperture Radar Imagery XV, 69700I (15 April 2008); https://doi.org/10.1117/12.777416
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KEYWORDS
Radar

Synthetic aperture radar

Transmitters

Image filtering

Radar imaging

Receivers

Data modeling

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