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.
