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Higher-order Rotation Vector Attitude Updating Algorithm

Published online by Cambridge University Press:  29 November 2018

Maosong Wang
Affiliation:
(National University of Defense Technology, Changsha, Hunan, P.R. China)
Wenqi Wu*
Affiliation:
(National University of Defense Technology, Changsha, Hunan, P.R. China)
Xiaofeng He
Affiliation:
(National University of Defense Technology, Changsha, Hunan, P.R. China)
Gongliu Yang
Affiliation:
(Science and Technology on Inertial Laboratory, Beihang University, Beijing, P.R. China)
Huapeng Yu
Affiliation:
(National Innovation Institute of Defense Technology, Academy of Military Sciences China, Beijing, P.R. China)

Abstract

Rotation vector-based attitude updating algorithms have been used as the mainstream attitude computation algorithms for many years. The most popular methodology for designing the rotation vector algorithm is by leveraging multiple samples of gyro integrated angular rate measurements. However, it has been pointed out by many researchers that the attitude updating accuracy is limited when using the multiple samples rotation vector algorithms, especially when the platforms work under high rate manoeuvres. The third-, fourth-, fifth- and sixth-order Picard component solutions of the rotation vector differential equation are given in this paper. A new design methodology for rotation vector-based attitude updating algorithms is proposed. Different vibratory dynamics and high rate manoeuvre roller coaster experiments were conducted to validate the effectiveness of the new algorithm. The results demonstrate the high accuracy of the new algorithm compared with conventional coning correction methods. The proposed algorithm can also be used in high accuracy attitude computation of a post-processing system, especially when the output frequency of the gyro is limited.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2018 

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References

REFERENCES

Bortz, J. E. (1971). A new mathematical formulation for strapdown inertial navigation. IEEE Transactions on Aerospace and Electronic Systems, 7(1), 6166.Google Scholar
Chen, X. and Tang, C. (2016). Improved class of angular rate-based coning algorithms. IEEE Transactions on Aerospace and Electronic Systems, 52(5), 22202229.Google Scholar
Ignagni, M. B. (1990). Optimal strapdown attitude integration algorithms. Journal of Guidance, Control, and Dynamics, 13(2), 363369.Google Scholar
Ignagni, M. B. (1996). Efficient class of optimized coning compensation algorithms. Journal of Guidance, Control, and Dynamics, 19(2), 424429.Google Scholar
Ignagni, M. (2012). Optimal sculling and coning algorithms for analog-sensor systems. Journal of Guidance Control and Dynamics, 35(3), 851.Google Scholar
Jiang, Y. F. and Lin, Y. P. (1992). Improved strapdown coning algorithms. IEEE Transactions on Aerospace and Electronic Systems, 28(2), 484490.Google Scholar
Kang, C. W., Cho, N. I. and Park, C. G. (2013). Approach to direct coning/sculling error compensation based on the sinusoidal modelling of IMU signal. IET Radar, Sonar and Navigation, 7(5), 527534.Google Scholar
Lee, J. G., Mark, J. G., Tazartes, D. A. and Yoon, Y. J. (1990). Extension of strapdown attitude algorithm for high-frequency base motion. Journal of Guidance, Control, and Dynamics, 13(4), 738743.Google Scholar
Miller, R. B. (1983). A new strapdown attitude algorithm. Journal of Guidance, Control, and Dynamics, 6(4), 287291.Google Scholar
Park, C. G., Kim, K. J., Lee, J. G. and Chung, D. (1999). Formalized approach to obtaining optimal coefficients for coning algorithms. Journal of Guidance, Control, and Dynamics, 22(1), 165168.Google Scholar
Savage, P. G. (2006). A unified mathematical framework for strapdown algorithm design. Journal of Guidance, Control, and Dynamics, 29(2), 237249.Google Scholar
Savage, P. G. (2010). Coning algorithm design by explicit frequency shaping. Journal of Guidance, Control, and Dynamics, 33(4), 1123.Google Scholar
Song, M., Wu, W. and Pan, X. (2013). Approach to recovering maneuver accuracy in classical coning algorithms. Journal of Guidance, Control, and Dynamics, 36(6), 18721880.Google Scholar
Wang, M., Wu, W., Wang, J. and Pan, X. (2015). High-order attitude compensation in coning and rotation coexisting environment. IEEE Transactions on Aerospace and Electronic Systems, 51(2), 11781190.Google Scholar
Wang, M., Wu, W. and He, X. (2018). Design and evaluation of high-order non-commutativity error compensation algorithm in dynamics. In Position, Location and Navigation Symposium (IEEE/ION PLANS), 3441.Google Scholar
Wu, Y. (2018). Rodfiter: attitude reconstruction from inertial measurement by functional iteration. IEEE Transactions on Aerospace and Electronic Systems, 54(5), 21312142.Google Scholar
Wu, Y., Cai, Q. and Truong, T. (2018). Fast RodFIter for Attitude Reconstruction from Inertial Measurements. IEEE Transactions on Aerospace and Electronic Systems, Early Access.Google Scholar
Yan, G. M., Yan, W. S. and Xu, D. M. (2008). Limitations of error estimation for classic coning compensation algorithm. Journal of Chinese Inertial Technology, 16(4), 380385.Google Scholar
Yan, G. M., Weng, J., Yang, X. K. and Qin, Y. Y. (2017). An accurate numerical solution for strapdown attitude algorithm based on Picard iteration. Journal of Astronautics, 38(12), 13081313.Google Scholar