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Publications about 'cross-track multibaseline synthetic aperture radar interferometric data'

Articles in journal or book chapters

  1. Christophe Magnard, Max Frioud, David Small, Thorsten Brehm, and Erich Meier. Analysis of a Maximum Likelihood Phase Estimation Method for Airborne Multibaseline SAR Interferometry. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(3):1072-1085, March 2016. Keyword(s): SAR Processing, SAR Interferometry, InSAR, Multibaseline Interferometry, Ka-band, Airborne SAR, Single-pass Multibaseline Interferometry, airborne radar, image texture, maximum likelihood estimation, millimetre wave radar, motion compensation, phase estimation, radar imaging, radar interferometry, synthetic aperture radar, C2F algorithm, ML method, airborne multibaseline SAR interferometry, calibration steps, coarse-to-fine algorithm, cross-track multibaseline synthetic aperture radar interferometric data, experimental Ka-band multibaseline system, homogeneous texture, imperfect motion compensation, maximum likelihood phase estimation method, noise level, Antenna measurements, Antennas, Calibration, Maximum likelihood estimation, Motion compensation, Phase estimation, Synthetic aperture radar, Interferometry, Ka-band, maximum likelihood (ML), millimeter wave radar, millimeterwave experimental multifrequency polarimetric high-resolution interferometric system (MEMPHIS), multibaseline, phase unwrapping, synthetic aperture radar (SAR). [Abstract] [bibtex-entry]


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Please note that access to full text PDF versions of papers is restricted to the Chair of Earth Observation and Remote Sensing, Institute of Environmental Engineering, ETH Zurich.
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This collection of SAR literature is far from being complete.
It is rather a collection of papers which I store in my literature data base. Hence, the list of publications under PUBLICATIONS OF AUTHOR'S NAME should NOT be mistaken for a complete bibliography of that author.




Last modified: Fri Feb 24 14:23:01 2023
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .


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