Author:
Mohammadkarimi H.,Mozafari S.,Alizadeh M. H.
Abstract
AbstractThis work introduces a novel approach to Strapdown Inertial Navigation System (SINS) alignment, distinct from recursive methods like Kalman filtering. The proposed methodology expedites bias error calculations by utilizing quaternion-based analytical relationships, which bypasses the slow convergence behavior associated with recursive algorithms, particularly in azimuth angle error estimation. In addition, the proposed approach demonstrates comparable accuracy to traditional fine alignment methods. Simulations and experiments validate that in contrast to the 10-min time requirement of traditional fine alignment methods (for azimuth angle estimation in stationary conditions), the proposed approach achieves the same accuracy within 20 s. However, limitations exist as the algorithm is applicable only in stationary conditions, and necessitating a high-grade IMU capable of measuring the earth’s rotation rate.
Publisher
Springer Science and Business Media LLC
Reference43 articles.
1. Rogers, R.M. Applied Mathematics in Integrated Navigation Systems. American Institute of Aeronautics and Astronautics (2003). https://books.google.de/books?id=dfS2WcYba9wC
2. Titterton, D., Weston, J.L., Electrical Engineers, I. & Aeronautics, A.I. Astronautics: Strapdown Inertial Navigation Technology. Institution of Engineering and Technology (2004). https://books.google.de/books?id=WwrCrn54n5cC
3. Zhou, H. & Ye, X. A Unified Initial Alignment Method of Sins based on FGO. IEEE Transactions on Industrial Electronics (2022)
4. Shen, C. et al. Seamless GPS/inertial navigation system based on self-learning square-root cubature Kalman filter. IEEE Trans. Industr. Electron. 68(1), 499–508 (2020).
5. Chen, Q., Lin, H., Kuang, J., Luo, Y. & Niu, X. Rapid initial heading alignment for mems land vehicular GNSS/INS navigation system. IEEE Sens. J. 23(7), 7656–7666 (2023).