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ORCID
N/A
Access Type
Open Access Thesis
Document Type
thesis
Degree Program
Electrical & Computer Engineering
Degree Type
Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)
Year Degree Awarded
2017
Month Degree Awarded
February
Abstract
A time-domain backprojection processor for airborne synthetic aperture radar (SAR) has been developed at the University of Massachusetts’ Microwave Remote Sensing Lab (MIRSL). The aim of this work is to produce a SAR processor capable of addressing the motion compensation issues faced by frequency-domain processing algorithms, in order to create well focused SAR imagery suitable for interferometry. The time-domain backprojection algorithm inherently compensates for non-linear platform motion, dependent on the availability of accurate measurements of the motion. The implementation must manage the relatively high computational burden of the backprojection algorithm, which is done using modern graphics processing units (GPUs), programmed with NVIDIA’s CUDA language. An implementation of the Non-Equispaced Fast Fourier Transform (NERFFT) is used to enable efficient and accurate range interpolation as a critical step of the processing. The phase of time- domain processed imagery is dif erent than that of frequency-domain imagery, leading to a potentially different approach to interferometry. This general purpose SAR processor is designed to work with a novel, dual-frequency S- and Ka-band radar system developed at MIRSL as well as the UAVSAR instrument developed by NASA’s Jet Propulsion Laboratory. These instruments represent a wide range of SAR system parameters, ensuring the ability of the processor to work with most any airborne SAR. Results are presented from these two systems, showing good performance of the processor itself.
DOI
https://doi.org/10.7275/9413831
First Advisor
Paul Robert Siqueira
Second Advisor
Ramakrishna Janaswamy
Recommended Citation
Lagoy, Dustin, "Time Domain SAR Processing with GPUs for Airborne Platforms" (2017). Masters Theses. 471.
https://doi.org/10.7275/9413831
https://scholarworks.umass.edu/masters_theses_2/471
Included in
Aerospace Engineering Commons, Geophysics and Seismology Commons, Signal Processing Commons