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• W2761506600 abstract "The ionospheric propagation path delay is a major error source in synthetic aperture radar (SAR) interferograms and, therefore, has to be estimated and corrected. Various methods can be used to extract different kinds of information about the ionosphere from SAR images, with different accuracies. This paper presents a general technique, based on a Bayesian inverse problem, that combines various information sources in order to increase the estimation accuracy, and thus the correction. A physically realistic fractal modeling of the ionosphere turbulence and a data-based estimation of the model parameters allow the avoidance of arbitrary filtering windows and coefficients. To test the technique, the differential ionospheric phase screen was estimated by combining the split-spectrum method with the azimuth mutual shifts between interferometric pair images. This combination is convenient since it can benefit from the strengths of both sources: range and azimuth variations from the split-spectrum method and small-scale azimuth variations from more sensitive azimuth shifts. Therefore, the two methods can recover the long and short wavelength components of the ionospheric phase screen, respectively. A theoretical comparison between the Faraday rotation method and the split-spectrum method is also reported. For the use in the combination, precedence was then given to the split-spectrum method because of the comparable precision level, lower susceptibility to biases, and wider applicability. Finally, Advanced Land Observing Satellite Phased Array type L-band SAR L-band images are used to show how the combined result is more accurate than that obtained with the simple split-spectrum method." @default.
• W2761506600 created "2017-10-20" @default.
• W2761506600 creator A5047436745 @default.
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• W2761506600 date "2017-11-01" @default.
• W2761506600 modified "2023-09-25" @default.
• W2761506600 title "Bayesian Data Combination for the Estimation of Ionospheric Effects in SAR Interferograms" @default.
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• W2761506600 doi "https://doi.org/10.1109/tgrs.2017.2730438" @default.
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