期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 59, 期 2, 页码 1285-1301出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2020.3003421
关键词
Strain; Fading channels; Time series analysis; Synthetic aperture radar; Systematics; Decorrelation; Moisture; Big Data; deformation estimation; differential interferometric synthetic aperture radar (SAR) (DInSAR); distributed scatterers (DSs); error analysis; near real-time (NRT) processing; phase inconsistencies; signal decorrelation; time-series analysis
类别
资金
- Russian Science Foundation [18-11-00136] Funding Source: Russian Science Foundation
This article investigates a new interferometric signal in multilooked SAR interferograms and discusses its impact on the estimation of Earth surface deformation. The study quantitatively assesses the contribution of this fading signal and evaluates its biasing impact on deformation-signal retrieval.
This article investigates the presence of a new interferometric signal in multilooked synthetic aperture radar (SAR) interferograms that cannot be attributed to the atmospheric or Earth-surface topography changes. The observed signal is short-lived and decays with the temporal baseline; however, it is distinct from the stochastic noise attributed to temporal decorrelation. The presence of such a fading signal introduces a systematic phase component, particularly in short temporal baseline interferograms. If unattended, it biases the estimation of Earth surface deformation from SAR time series. Here, the contribution of the mentioned phase component is quantitatively assessed. The biasing impact on the deformation-signal retrieval is further evaluated. A quality measure is introduced to allow the prediction of the associated error with the fading signals. Moreover, a practical solution for the mitigation of this physical signal is discussed; special attention is paid to the efficient processing of Big Data from modern SAR missions such as Sentinel-1 and NISAR. Adopting the proposed solution, the deformation bias is shown to decrease significantly. Based on these analyses, we put forward our recommendations for efficient and accurate deformation-signal retrieval from large stacks of multilooked interferograms.
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