Paper
25 July 2022 Using U-Net for signal preprocessing in interferometric synthetic aperture radar
Author Affiliations +
Proceedings Volume 12295, Optical Technologies for Telecommunications 2021; 122950S (2022) https://doi.org/10.1117/12.2631723
Event: Nineteenth International Scientific and Technical Conference "Optical Technologies for Communications", 2021, Samara, Russian Federation
Abstract
Synthetic Aperture Radar (SAR) interferometry is an active remote sensing technology that uses microwaves to characterize the earth's surface. SAR interferometry allows to measure the 3D profile of the earth's surface, recover surface topography, and determine topographic displacements over time. The microwave SAR signal is usually highly distorted. Distortions can be caused by, for example, atmospheric disturbances and various characteristics of earth's surface scatterers reflectance. Compensation for these distortions is performed by filtering the phase and evaluating the degree of coherence of the original images. This is an important step to improve the accuracy of the subsequent pphase-unwrapping operation. In this paper, we investigate the use of U-net neural networks for preprocessing the SAR interferogram at various parameters of the distortion of the SAR signal. Two neural networks filter the SAR interferogram and determine the degree of coherence, respectively.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
P. G. Serafimovich, A. P. Dzyuba, S. N. Khonina, and S. B. Popov "Using U-Net for signal preprocessing in interferometric synthetic aperture radar", Proc. SPIE 12295, Optical Technologies for Telecommunications 2021, 122950S (25 July 2022); https://doi.org/10.1117/12.2631723
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KEYWORDS
Synthetic aperture radar

Interferometry

Phase interferometry

Coherence (optics)

Image filtering

Neural networks

Interferometric synthetic aperture radar

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