Master-Slave INS Transfer Alignment Based on State-Transformation Extended Kalman Filter
- Resource Type
- Conference
- Authors
- Wang, Yuxin; Wang, Maosong; Cui, Jiarui; Tang, Kanghua
- Source
- 2023 China Automation Congress (CAC) Automation Congress (CAC), 2023 China. :2579-2584 Nov, 2023
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Location awareness
Fuses
Filtering
Inertial navigation
Main-secondary
Robustness
Trajectory
transfer alignment
velocity-attitude-position based transfer alignment
state-transformation extended Kalman filter
- Language
- ISSN
- 2688-0938
In this study, a fast transfer alignment algorithm that fuses the velocity-attitude-position of the Master-Slave INS is proposed. A state-transformation extended Kalman filter (ST-EKF) with better filtering robustness is used instead of the conventional extended Kalman filter (EKF) for the transfer alignment of the Master-Slave INS. The accuracy of the proposed algorithm is verified by three sets of on-board field transfer alignment experiments under different maneuvering trajectories. The results show that the proposed ST -EKF -based transfer alignment algorithm has higher alignment accuracy and faster convergence speed, and the 180s localization accuracy RMSE of the ST-EKF algorithm is improved by 23.29% on average compared to the EKF algorithm.