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Title
Topography measurements using an airborne Ka-band FMCW Interferometric Synthetic Aperture Radar
Author ORCID Identifier
N/A
AccessType
Open Access Dissertation
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Electrical and Computer Engineering
Year Degree Awarded
2017
Month Degree Awarded
February
First Advisor
Paul Siqueira
Subject Categories
Electrical and Electronics | Electromagnetics and Photonics | Signal Processing
Abstract
Radar interferometry at millimeter-wave frequencies has the ability of topography measurement of different types of terrain, such as water surfaces and tree canopies. A Ka-band interferometric radar was mounted on an airborne platform, and flown over the Connecticut river region in western Massachusetts near Amherst on June 11, 2012. More than 20 Gigabytes of raw data was recorded. This dissertation outline presents the results of the data processing, which includes (1) the estimation and removal of the embedded high frequency phase error in the raw data; (2) the synthetic aperture processing; (3) the interferometric processing. The digital elevation model (DEM) has been generated based on an external DEM from MassGIS. The accuracy of the topography measurement can be affected by many factors, such as the de-correlation between channels and the residual phase error. This dissertation outline proposes to evaluate the accuracy of the topography measurement by quantifying each error source. Specifically, the performance of the phase error estimator and the Doppler centroid estimation will be analyzed, and an algorithm which estimates the attitudes of the airborne platform will be developed.
DOI
https://doi.org/10.7275/9478391.0
Recommended Citation
Fu, Kan, "Topography measurements using an airborne Ka-band FMCW Interferometric Synthetic Aperture Radar" (2017). Doctoral Dissertations. 876.
https://doi.org/10.7275/9478391.0
https://scholarworks.umass.edu/dissertations_2/876
Included in
Electrical and Electronics Commons, Electromagnetics and Photonics Commons, Signal Processing Commons