Mitigation of time-series InSAR turbulent atmospheric phase noise: A review

Geodesy and Geodynamics(2022)

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摘要
Synthetic Aperture Radar (SAR) interferometry is one of the most powerful remote sensing tools for ground deformation detection. However, tropospheric delay greatly limits the measurement accuracy of the InSAR technique. While vertically stratified tropospheric delays have been extensively investigated and well tackled, turbulent tropospheric phase noise still remains an intractable issue. In recent years, great efforts have been made to reduce the influence of turbulent atmospheric delay. This contribution is intended to provide a systematic review of the progress achieved in this field. First, it introduces the physical characteristics of atmospheric signals in interferograms. Then, a review of the main mitigation algorithms proposed in the literature is provided. In addition, the strengths and weaknesses of each approach are analyzed to provide guidance for choosing a suitable method accordingly. Finally, suggestions for resolving the challenging issues and an outlook for future research are given.
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关键词
InSAR,Turbulent atmospheric phase,Variance and covariance matrix,Stochastic model,Deep learning
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