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Volumetric synthetic aperture radar (VolSAR) analysis techniques and image formation algorithms suitable for short ranges and large scenes are presented. From a diffractive wave field inversion perspective, ultrawide beamwidth and near range SAR imaging scenarios can be viewed as a form of in situ SAR. Novel Huygens–Fresnel processing methods are introduced that empower in situ volumetric imaging with 2-D and 3-D aperture synthesis. These methods support coherent fusion across multiple separated frequency bands and also support spatial subaperture fusion of data from sparse sensor swarms. A novel signal analysis tool we call a chirp couplet is developed and shown to be useful in the expression and exploitation of temporal and spatial SAR chirp signals. Chirp couplets provide a physically motivated and unifying tool for both temporal and spatial elements in SAR signal analysis. In the temporal domain, chirp couplets provide a generalized formulation of the coupling of time and frequency that exists, for example, in linear frequency modulated waveforms. In the spatial domain, chirp couplets describe the coupling of sensor position and sensed wavenumber. Formulations of chirp couplets suitable for ray tomographic SAR algorithms (i.e., polar format algorithms) are contrasted with chirp couplets capable of supporting diffractive tomographic SAR algorithms (i.e., Stolt format algorithms). Scenarios in which diffraction limited resolution can be achieved with in situ VolSAR and finite length synthetic apertures are explored. VolSAR imaging methods are shown to escape the approximations that constrain the application and performance of range-Doppler and polar format methods. [ABSTRACT FROM AUTHOR]

Fourier analysis-based focusing of synthetic aperture radar (SAR) data collected during circular flight path is a recent advancement in SAR signal processing. This paper uses the House-holder transform to obtain a ground plane circular SAR (CSAR) signal phase history from the slant plane CSAR phase history by inverting the linear shift-varying system model, thereby circumventing the need for explicitly computing a pseudo-inverse. The Householder transform has recently been shown to have improved error bounds and stability as an underdetermined and ill-conditioned system solver, and the Householder transform is computationally efficient. [ABSTRACT FROM AUTHOR]