A Quaternion Scaled Unscented Kalman Estimator for Inertial Navigation States Determination Using INS/GPS/Magnetometer Fusion


This Inertial Navigation System (INS), Global Positioning System (GPS) and fluxgate magnetometer technologies have been widely used in a variety of positioning and navigation applications. In this paper, a low cost solid state INS/GPS/Magnetometer integrated navigation system has been developed that incorporates measurements from an Inertial Navigation System (INS), Global Positioning System (GPS) and fluxgate magnetometer (Mag.) to provide a reliable complete navigation solution at a high output rate. The body attitude estimates, especially the heading angle, are fundamental challenges in a navigation system. Therefore targeting accurate attitude estimation is considered a significant contribution to the overall navigation error. A better estimation of the body attitude estimates leads to more accurate position and velocity estimation. For that end, the aim of this research is to exploit the magnetometer and accelerometer data in the attitude estimation technique. In this paper, a Scaled Unscented Kalman Filter (SUKF) based on the quaternion concept is designed for the INS/GPS/Mag integrated navigation system under large attitude error conditions. Simulation and experimental results indicate a satisfactory performance of the newly developed model.

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Khoder, W. and Jida, B. (2014) A Quaternion Scaled Unscented Kalman Estimator for Inertial Navigation States Determination Using INS/GPS/Magnetometer Fusion. Journal of Sensor Technology, 4, 101-117. doi: 10.4236/jst.2014.42010.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Grewal, M.S., Weill, L.R. and Andrews, A.P. (2001) Global Positioning Systems, Inertial Navigation, and Integration. John Wiley & Sons, Inc., Hoboken.
[2] Rogers, R.M. (2003) Applied Mathematics in Integrated Navigation Systems. 2nd Edition, AIAA Education Series, Reston.
[3] Salychev, O. (2004) Applied Inertial Navigation: Problems and Solutions. BMSTU Press, Moscow.
[4] Titterton, D.H. and Weston, J.L. (2004) Strapdown Inertial Navigation Technology. 2nd Edition, AIAA Education Series, Reston.
[5] Kong, X. (2004) INS Algorithm Using Quaternion Model for Low Cost IMU. Robotics and Autonomous Systems, 46, 221-246.
[6] Shin, E.-H. (2005) Estimation Techniques for Low-Cost Inertial Navigation. UCGE Reports Number 20219. The University of Calgary, Calgary.
[7] Crassidis, J.L. (2006) Sigma-Point Kalman Filtering for Intagrated GPS and Inertial Navigation. IEEE Transactions on Aerospace and Electronic Systems, 42, 750-756.
[8] Ali, S. and El-Sheimy, N. (2013) Low-Cost MEMS-Based Pedestrian Navigation Technique for GPS-Denied Areas. Hindawi Publishing Corporation. Journal of Sensors, 2013, Article ID: 197090.
[9] Zhang, P., Gu, J., Milios, E.E. and Huynh, P. (2005) Navigation with IMU/GPS/Digital Compass with Unscented Kalman Filter. Proceedings of the IEEE International Conference on Mechatronics & Automation, Niagara Falls, July 2005, Vol. 3, 1497-1502.
[10] Shuster, M.D. (1993) A Survey of Attitude Representations. Journal of the Astronautical Sciences, 41, 439-517.
[11] Crassidis, J.L. and Markley, F.L. (2003) Unscented Filtering for Spacecraft Attitude Estimation. Journal of Guidance, Control, and Dynamics, 26, 536-542.
[12] Markley, F.L. (2003) Attitude Error Representations for Kalman Filtering. Journal of Guidance, Control, and Dynamics, 26, 311-317.
[13] Miller, R.B. (1983) A New Strapdown Attitude Algorithm. Journal of Guidance and Control, 6, 287-291.
[14] Waldmann, J. (2002) Attitude Determination Algorithms, Computational Complexity, and the Accuracy of Terrestrial Navigation with Strap down Inertial Sensors. 14th Congress Brasileiro de Automatica, Natal-RN, 2-5 September 2002, 2367-2373.
[15] Hiliuta, A., Landry Jr., R. and Gagnon, F. (2004) Fuzzy Correction in a GPS/INS Hybrid Navigation System. IEEE Transactions on Aerospace and Electronic Systems, 40, 591-600.
[16] Khoder, W. (2010) Contribution à la navigation linéaire par filtrage non linéaire et approche floue. Ph.D. Dissertation, ULCO University, Calais.
[17] He, X., Chen, Y. and Iz, H.B. (1998) A Reduced-Order Model for Integrated GPS/INS. IEEE AES Systems Magazine, 40-45.
[18] Touil, K. and Ghadi, A. (2012) Bayesian Bootstrap Filter Approach for GPS/INS Integration. International Journal of Networks and Systems, 1.
[19] Gautier, J.D. (2003) GPS/INS Generalized Evaluation Tool (GIGET) for the Design and Testing of Integrated Navigation Systems. Ph.D. Dissertation, Department of Aeronautics and Astronautics, Stanford University, Stanford.
[20] Khoder, W., Fassinut-Mombot, B. and Benjelloun, M. (2008) Inertial Navigation Attitude Velocity and Position Algorithms Using Quaternion Scale Unscented Kalman Filtering. The 34 Annual Conference on Information of the IEEE Industrial Electronics Society, 10-13 November 2008, Orlando, 1754-1759.
[21] Khoder, W., Fassinut-Mombot, B. and Benjelloun, M. (2008) Quaternion Unscented Kalman Filtering for Integrated Inertial Navigation and GPS. The 11th International Conference on Information Fusion, Cologne, 30 June-3 July 2008, 1-8.
[22] Vasconcelos, J.F., Calvário, J., Oliveira, P. and Silvestre, C. (2004) GPS Aided IMU Unmanned Air Vehicles. Proceedings of the 5th IFAC/EURON Symposium on Intelligent Autonomous Vehicles, Instituto Superior Técnico, Lisboa, 5-7 July 2004, 1-6.
[23] Oh, S.M. (2007) Nonlinear Estimation Techniques for Vision-Based Air-to-Air Tracking. School of Aerospace Engineering, Georgia Institute of Technology, Atlanta.
[24] Julier, S.J. and Uhlmann, J.K. (1997) A New Extension of the Kalman Filter to Nonlinear Systems. Multi Semsor Fusion, Tracking and Resource Management, II SPIE, Orlando, April 1997, Vol. 3068, 182-193.
[25] Wan, E.A. and van der Merwe, R. (2001) The Unscented Kalman Filter. In: Haykin, S., Ed., Kalman Filtering and Neural Networks, Wiley, New York, 221-280.
[26] Julier, S.J. and Uhlmann, J.K. (2004) Reduced Sigma Point Filters for the Propagation of Means and Covariances through Nonlinear Transformations. Proceedings of the IEEE, 92, 401-422.
[27] 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.
[28] Julier, S.J. (2003) The Spherical Simplex Unscented Transformation. Proceedings of the American Control Conference (ACC ‘03), Denver, 4-6 June 2003, Vol. 3, 2430-2434.

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