| Citation: |
XU Fu, WANG Zheng, LI Zhenhong, LI Yongsheng. An Atmospheric Correction Method for Ground-Based Radar Under Complex Environment[J]. Geomatics and Information Science of Wuhan University, 2023, 48(12): 2069-2081. DOI: 10.13203/j.whugis20220466
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The ground-based radar has features such as working all-time in all-weather, providing continuous observations with high spatiotemporal resolutions and can monitor landslides with high precision in near real-time. However, atmospheric effects represent one major limitation of ground-based radar, due to the spatiotemporal variations of the troposphere, especially in mountainous areas. Atmospheric variations are often treated as static signals and corrected by the range function model which can be unreliable, particularly when strong dynamic atmospheric turbulence occurs.
Based on its successful experience in the generic atmospheric correction online service for interferometric synthetic aperture radar (InSAR), the ground based iterative tropospheric decomposition (GBITD) model is utilized to decompose the tropospheric delay into stratification and turbulence components, and perform atmospheric correction. The GBITD model doesn't require global navigation satellite system or any external meteorological observations, which makes it flexible for InSAR atmospheric correction.
The application of the GBITD model to the 2018 Baige landslide suggests that the root mean square of two interferograms with temporal baselines of 2 min and 10 min decreased from 1.43 mm and 1.69 mm to 0.21 mm and 0.24 mm, respectively. The maximum cumulative displacement derived from the 778 images acquired during the period from 4 to 10 December 2018 was 1.4 m with the maximum displacement rate of 0.23 m/d.
The experimental results show that the GBITD method performes best compared against the homogeneous model and the stratified model in complex mountainous areas. Furthermore, Ground-based radar has obvious unique advantages in landslide monitoring, which can provide strong technical support for landslide emergency monitoring and risk assessment.
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