A Loose Integration of High-Rate GNSS and Strong-Motion Records with Variance Compensation Adaptive Kalman Filter for Broadband Co-Seismic Displacements
Source abstract
Abstract
The loose integration system of high-rate GNSS and strong-motion records based on Kalman filtering technology is currently a research focus for capturing broadband co-seismic displacements. To address the problem of time-varying system noise variance in the standard Kalman filter (SKF), a variance compensation adaptive Kalman filter (VC-AKF) was adopted in this study to obtain more accurate high-precision broadband co-seismic displacement and provide reliable data support for seismic scientific research and practical applications. The algorithm continuously updates the system noise variance and calculates the state vector by collecting prediction residuals in real time. To verify the effectiveness and superiority of this method, a numerical simulation and a seismic experiment from the 2017 Ms 7.0 Jiuzhaigou earthquake were carried out for comparative analysis. Based on the simulation results, the precision of the proposed algorithm was 46% higher than that of the SKF. The seismic experiment results indicate that the proposed VC-AKF approach can eliminate the baseline shift of accelerometers and weaken the influence of time-varying system noise variance towards more robust displacement information.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Seismology and Earthquake Studies · GNSS positioning and interference · earthquake and tectonic studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, 1 Zhanlanguan Road, Beijing 100044, China
Funding
National Natural Science Foundation of China · Beijing Key Laboratory of Urban Spatial Information Engineering
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