Spiral SAR Imaging with Fast Factorized Back-Projection: A Phase Error Analysis

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.

An Efficient Backprojection Algorithm Based on Wavenumber-Domain Spectral Splicing for Monostatic and Bistatic SAR Configurations

“…On the basis of the FBP algorithm, fast factorized backprojection based on aperture factorization (FFBP) is proposed [17] to further increase the calculation speed. However, the coordinate system still needs to be re-established during sub-aperture fusion [18,19], and multiple searches and projections are required, which results in a large amount of computation.…”

“…Suppose that the transmitting station transmits a beam of signal at t 1 , the position is (x t1 , y t1 , z t1 ), and the receiving station receives the echo at t 2 , and the position is (x r2 , y r2 , z r2 ). t 2 and (x r2 , y r2 , z r2 ) can be obtained from Formula (19). Suppose that the position of a pixel point pixel_A in the imaging area is (α p , r p ), where α p is the polar angle and r p is the polar diameter, then the instantaneous slant range from the transmitting station to a pixel point pixel_A in the imaging scene when transmitting the signal is…”