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Improvement of Real-Time Kinematic Positioning Using Kalman Filter-Based Singular Spectrum Analysis During Geomagnetic Storm for Thailand Sector
Author(s)
Date Issued
January 1, 2023
Type
Book Chapter
Abstract
The ionospheric error is the largest error source of positioning, especially when electron density becomes high during geomagnetic storms. Real-time kinematic (RTK) positioning during the storm time often has higher fluctuation and noise errors in positioning. Therefore, in this work, a technique based on Kalman filter with implementation of singular spectrum analysis (namely KF-SSA) is anticipated for RTK positioning. The RTK drone data are collected around 50 min of interval (7.37 AM to 8.28 AM) on May 12, 2021, with respect to a base station located at 13.84° N, 100.29° E. The RTK positioning tests have been done to determine the positioning accuracy of the proposed algorithm. The simulated results reveal that SSA implication with KF showed very high-precision estimates and improves the positioning accuracy.
Citation
Lecture Notes in Networks and Systems, 551, 79-87, 2023