Fusion of InSAR and GNSS Based on Adaptive Spatio-Temporal Kalman Model for Reconstructing High Spatio-Temporal Resolution Deformation

• Published in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Main Authors: Peiling Li, Zhiwei Li, Wenxiang Mao, Qiang Shi, Qiwei Lin
• Format: Article
• Language: English
• Published: IEEE 2024-01-01
• Subjects: Data fusion; global navigation satellite system (GNSS); ground deformation monitoring; interferometric synthetic aperture radar (InSAR); spatio-temporal Kalman
• Online Access: https://ieeexplore.ieee.org/document/10720337/
• ISSN: 1939-1404; 2151-1535

With the help of interferometric synthetic aperture radar (InSAR) and global navigation satellite system (GNSS) technology, high spatial and temporal resolution surface deformation results can be generated, which can help to better understand the mechanism of surface deformation. The spatio-temporal Kalman-based InSAR and GNSS fusion method fully considers the spatio-temporal correlation of deformation and characterizes the potential spatio-temporal process of deformation through spatial modeling and Kalman filter or smooth. However, when focusing on deformation with typical subsidence spatial characteristics, existing studies did not fully consider the spatial distribution of deformations, resulting in the loss of spatial detail information. This article proposes an adaptive spatial modeling optimization method that takes into account the spatial distribution of deformation, which can capture the optimal spatial basis layout scheme under a limited number of spatial bases, establish a more accurate spatial model, and improve the accuracy of deformation fusion. The effectiveness and reliability of this method are verified through simulation experiments and the deformation monitoring results in Datong City, China. The results of the two experiments show that the proposed method can improve the accuracy of InSAR interpolation results by 27.7% and 11.5% on average, respectively.