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 narrowband waveforms in the case when the targets are moving slowly relative to the speed of light. From this model, 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 phase-space point-spread function (PSF). We show plots of the phase-space point-spread function for various geometries. We also show that in special cases, the theory reduces to: 1) range-Doppler imaging, 2) inverse synthetic aperture radar (ISAR), 3) synthetic aperture radar (SAR), 4) Doppler SAR, and 5) tomography of moving targets.
Did you like this research project?
To get this research project Guidelines, Training and Code... Click Here