Abstract
This paper presents a fast factorized back-projection (FFBP) algorithm that can satisfactorily process real P-band synthetic aperture radar (SAR) data collected from a spiral flight pattern performed by a drone-borne SAR system. Choosing the best setup when processing SAR data with an FFBP algorithm is not so straightforward, so predicting how this choice will affect the quality of the output image is valuable information. This paper provides a statistical phase error analysis to validate the hypothesis that the phase error standard deviation can be predicted by geometric parameters specified at the start of processing. In particular, for a phase error standard deviation of ~12°, the FFBP is up to 21 times faster than the direct back-projection algorithm for 3D images and up to 13 times faster for 2D images.
Highlights
In synthetic aperture radar (SAR) imaging, circular flight path surveys produce 2D images with very high resolution as data are collected over 360◦ around the imaged area
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An improved version of the fast factorized back-projection (FFBP) algorithm [21] could successfully process real P-band SAR data acquired by a drone-borne SAR system that performed a spiral flight pattern
Summary
In synthetic aperture radar (SAR) imaging, circular flight path surveys produce 2D images with very high resolution as data are collected over 360◦ around the imaged area. Multicircular SAR, or holographic SAR tomography (HoloSAR), creates another synthetic aperture in elevation that mitigates these undesirable sidelobes, providing complete 3D data reconstruction with very high resolution [4,5,6,7,8,9]. The sparse nature of the elevation aperture in HoloSAR poses some difficulties for a system working in the THz band [10]. These issues are overcome with a cylindrical spiral flight pattern with constant vertical speed
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