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Marginalized Unscented Quaternion Estimator for Integrated INS/GPS

Published online by Cambridge University Press:  07 March 2016

Fangneng Li ,
Lubin Chang ,
Baiqing Hu  and
Kailong Li
Fangneng Li
Affiliation:
(Department of Navigation Engineering, Naval University of Engineering, Wuhan 430033, China)
Lubin Chang*
Affiliation:
(Department of Navigation Engineering, Naval University of Engineering, Wuhan 430033, China)
Baiqing Hu
Affiliation:
(Department of Navigation Engineering, Naval University of Engineering, Wuhan 430033, China)
Kailong Li
Affiliation:
(Department of Navigation Engineering, Naval University of Engineering, Wuhan 430033, China)
*
(E-mail: [email protected])
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Abstract

The UnScented QUaternion Estimator (USQUE) has been approved as a promising substitute for the extended Kalman filter when applied in the Standard Inertial Navigation Equations (SINE)-based inertial navigation system/global positioning system integration. However, the expensive computational burden makes it untenable in real time applications. In this paper, a computationally efficient filtering algorithm called Marginalised USQUE (MUSQUE) is derived by embedding the Marginalised Unscented Transformation (MUT) that is applicable to nonlinear systems with a linear substructure into the widely used USQUE. The contributions of the MUSQUE developed here are twofold. Firstly, the SINE are reconstructed to be only nonlinear in the attitude quaternion while linear in velocity and position, which makes the MUT potentially applicable in the USQUE. Secondly, the quaternion and generalised Rodrigues parameter-based sigma points are propagated simultaneously in the MUSQUE to deal with the dimensional mismatching hierarchy of the USQUE. Compared with the USQUE the number of sigma points can be decreased substantially, thereby making the applied MUSQUE computationally tenable. The experimental results show that the proposed MUSQUE has nearly identical performance with the USQUE but with much reduced computational burden.

Keywords

INS/GPS integrationMarginalised unscented transformationQuaternionUnScented QUaternion Estimator
Type
Research Article
Information
The Journal of Navigation , Volume 69 , Issue 5 , September 2016 , pp. 1125 - 1142
Copyright
Copyright © The Royal Institute of Navigation 2016 

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References

REFERENCES

Anderson, B. D. O. and Moore, J. B. (1979). Optimal filtering, Prentice-hall Englewood Cliffs, NJ.Google Scholar
Chang, G. B. (2014). Loosely Coupled INS/GPS Integration with Constant Lever Arm using Marginal Unscented Kalman Filter. Journal of Navigation, 67, 419–436.Google Scholar
Chang, L. B., Hu, B. Q. and Chang, G. B. (2014). Modified UnScented QUaternion Estimator based on Quaternion Averaging. Journal of Guidance, Control, and Dynamics, 37, 305–309.Google Scholar
Chang, L. B., Hu, B. Q., Li, A. and Qin, F. J. (2013). Transformed unscented Kalman filter. IEEE Transactions on Automatic Control, 49, 252–257.Google Scholar
Crassidis, J. L. (2006). Sigma-point Kalman filtering for integrated GPS and inertial navigation. IEEE Transactions on Aerospace and Electronic Systems, 42, 750–756.Google Scholar
Crassidis, J. L. and Markley, F. L. (2003). Unscented filtering for spacecraft attitude estimation. Journal of Guidance, Control, and Dynamics, 26, 536–542.Google Scholar
Crassidis, J. L., Markley, F. L. and Cheng, Y. (2007). Survey of Nonlinear Attitude Estimation. Journal of Guidance, Control, and Dynamics, 30, 12–28.Google Scholar
Groves, P. D. (2008). Principles of GNSS, Inertial, and Multi-sensor Integrated Navigation Systems. Artech House.Google Scholar
Julier, S. J. and Uhlmann, J. K. (2004). Unscented filtering and nonlinear estimation. Proc. IEEE, 92, 401–422.CrossRefGoogle Scholar
Julier, S. J., Uhlmann, J. K. and Durrant-Whyte, H. F. (2000). A new method for the nonlinear transformation of means and covariances in filters and estimators. IEEE Transactions on Automatic Control, 45, 477–482.CrossRefGoogle Scholar
Markley, F. L. (2003). Attitude error representations for Kalman filtering. Journal of Guidance , Control, and Dynamics, 26, 311–317.CrossRefGoogle Scholar
Markley, F. L., Cheng, Y., Crassidis, J. L. and Oshman, Y. (2007). Averaging Quaternions. Journal of Guidance, Control, and Dynamics, 30, 1193–1196.Google Scholar
Miller, , and Campbell, M. (2012). Sensitivity Analysis of a Tightly-Coupled INS/GPS System for Autonomous Navigation. IEEE Transactions on Aerospace and Electronic Systems, 48, 1115–1135.Google Scholar
Morelande, M. R. and Moran, B. (2007). An unscented transformation for conditionally linear models. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Honolulu, HI, USA.Google Scholar
Morelande, M. R. and Ristic, B. (2008). Smoothed State Estimation for Nonlinear Markovian Switching Systems. IEEE Transactions on Aerospace and Electronic Systems, 44, 1309–1324.Google Scholar
Nordlund, P-J. and Gustafsson, F. (2004). Marginalized Particle Filter for Accurate and Reliable Terrain-Aided Navigation. IEEE Transactions on Aerospace and Electronic Systems, 45, 1385–1399.CrossRefGoogle Scholar
Särkkä, S. (2013). Bayesian Filtering and Smoothing, Cambridge University Press.Google Scholar
Semper, S. R., Crassidis, J. L., Jemin George, J., Mukherjee, S. and Singla, P. (2015). Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation. Journal of Guidance, Control, and Dynamics, 38, 1291–1295.Google Scholar
Sun, D., Petovello, M. G. and Cannon, M. E. (2013). Ultratight GPS/Reduced-IMU Integration for Land Vehicle Navigation. IEEE Transactions on Aerospace and Electronic Systems, 49, 1781–1791.Google Scholar
Zhang, Q., Meng, X., Zhang, S. and Wang, Y. (2015). Singular Value Decomposition-based Robust Cubature Kalman Filtering for an Integrated GPS/SINS Navigation System. Journal of Navigation, 68, 549–562.CrossRefGoogle Scholar
Zhou, J., Knedlik, S. and Loffeld, O. (2010). INS/GPS tightly-coupled integration using adaptive unscented particle filter. The Journal of Navigation, 63, 491–513.CrossRefGoogle Scholar
Zhou, J., Yang, Y., Zhang, J., Edwan, E. and Loffeld, O. (2011). Tightly-coupled INS/GPS using Quaternion-based Unscented Kalman filter. AIAA Guidance, Navigation and Control, Portland, Oregon, USA.Google Scholar