- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
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| Citation: | HUANG Qihuan, HE Ziqi, YUE Jiawei, ZHANG Hanwen. InSAR Tropospheric Correction Method Incorporating Baarda Data Snooping and Its Application[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230703
|
To investigate the impact of turbulent atmospheric delay on high-precision and fine-scale deformation extraction using time-series InSAR (Interferometric Synthetic Aperture Radar), the turbulent atmospheric delay was considered as a gross error in the time series, based on its random characteristics in the spatiotemporal domain and its significant impact on deformation phase. The Baarda data snooping method was first applied to identify and remove the turbulent atmospheric delay, followed by spatiotemporal filtering to extract high-precision deformation information. Simulation and Sentinel-1 SAR data have confirmed the effectiveness of the proposed method. Results show that compared to using only spatiotemporal filtering, the standard deviation of displacement rate residuals obtained from the simulated data using the proposed method is decreased by about 25.8% and 16.0% in the stable and deformation regions, respectively. For Sentinel-1 SAR data, the semi-variograms of the results are reduced by about 74% compared to the original phase at the same spatial scale, outperforming the 65% reduction achieved by spatiotemporal filtering alone. The proposed method has been successfully applied to the fine-scale monitoring of the Orange Line rail transit in Lahore, Pakistan, with 17.6% of the entire line found to be located in areas experiencing strong ground subsidence.
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HUANG Qihuan, HE Ziqi, YUE Jiawei, ZHANG Hanwen. InSAR Tropospheric Correction Method Incorporating Baarda Data Snooping and Its Application[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230703
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