Factorized Geometrical Autofocus for UWB UHF-band SAR with a GPS-supported Linear Track Model
Journal article, 2022

This paper describes how to form a SAR image without proper motion quantities. That is within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a fast-factorized back-projection formulation with adjustable geometry parameters. Sub-apertures are tuned and merged pair by-pair (base-2) and step-by-step. With this technique, we can correct an erroneous geometry and form a focused image. The FGA algorithm has been applied on two data sets, acquired by the UWB CARABAS 3 system at UHF-band. The tracks are measured accurately by means of a DGPS. We however adopt and modify a geometry model. Equidistant linear tracks at fixed altitudes are assumed. These tracks are then regulated via a two-stage search strategy and a reverse processing procedure. As this is a first experiment at UHF-band, we provide GPS-based length values for the sub-apertures, to simplify the search. Multiple geometry solutions are tested for each sub-aperture pair, i.e. at each resolution level. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a focused image with wavelength resolution at UHF-band, i.e. with minimum support from a motion measurement system.

SAR

Global Positioning System

Image resolution

Tracking

Electronics packaging

Geometry

back-projection

Azimuth

Apertures

FGA

Autofocus

Author

Jan Torgrimsson

Microwave and Optical Remote Sensing

Patrik Dammert

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Saab

H. Hellsten

Halmstad University

Saab

Lars Ulander

Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing

Swedish Defence Research Agency (FOI)

IEEE Transactions on Aerospace and Electronic Systems

0018-9251 (ISSN) 15579603 (eISSN)

Vol. 58 4 3147-3161

Subject Categories

Signal Processing

Computer Vision and Robotics (Autonomous Systems)

Medical Image Processing

DOI

10.1109/TAES.2022.3149235

More information

Latest update

3/7/2024 9