Performance Analysis of Medium Accuracy FOG-Based IMU Integrated with Optical Odometer for Land Vehicle Navigation

Abstract:

The aim of this work is to research the feasibility of using optical odometer as the aided sensor for accuracy improvement of medium accuracy (FOG)-based IMU for land vehicle navigation. Usually GNSS is integrated with low cost SINS (strapdown inertial navigation systems) for land vehicle navigation but GNSS is not always reliable in land vehicle applications. The focus is on analysis of position and velocity accuracy of SINS/Odometer integration using close loop kalman filter. Integrated navigation algorithm for vehicle states estimation and correction have been designed and implemented. The measurement error model for odometer in navigation frame is developed for Kalman filter implementation. As the prior knowledge of measurement noise which represents the stochastic properties of odometer is not exactly known, so an adaptive Kalman filter (AKF) is also proposed for online estimation of the measurement noise matrix in order to improve the accuracy. For the performance analysis of the designed system, field test is carried out and results show that the accuracy of the medium accuracy fiber optics gyro (FOG)-based SINS is improved and the systems is capable for land vehicle navigation application

• Periodical: Applied Mechanics and Materials (Volume 245)
• Pages: 334-339
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.245.334
• Online since: December 2012
• Authors: Muhammad Ilyas, Ren Zhang, Qiu Shi Qian, Yun Chun Yang
• Keywords: Adaptive Kalman Filter, FOG IMU, Integration, Land Vehicle Navigation, Odometer

References

[1] J. Lobo, P. Lucas, J. Dias, and A. T. D. Almeida, "Inertial Navigation System for Mobile Land Vehicles," Proc. IEEE IntPress, vol. 2, pp.843-848, 1995.

DOI: 10.1109/isie.1995.497296

[2] J. Titterton, D.H. Weston, Strapdown Inertial Navigation Technology. Peter Pereguin, London, 1997.

[3] J. A. Farrel, Aided Navigation: GPS with High Rate Sensors. The McGraw Hill, 2008.

[4] E. M. Hemerly, "IMPLEMENTATION OF A GPS / INS / ODOMETER NAVIGATION SYSTEM," in Mechatronics, 2008, vol. 3, pp.519-524.

[5] A. H. Mohamed and K. P. Schwarz, "Adaptive Kalman Filtering for INS/GPS," Journal of Geodesy, vol. 73, no. 4, pp.193-203, 1999.

DOI: 10.1007/s001900050236

[6] E. H. Shin, "Estimation Techniques for Low-Cost Inertial Navigation," Department of Geomatics Engineering, University of Calgary, 2005.

[7] M. G. Petovello, "Real-Time Integration of a Tactical-Grade IMU and GPS for High-Accuracy Positioning and Navigation," Department of Geomatics Engineering, University of Calgary,, 2003.

[8] R. Mehra, "On the Identification of Variance and Adaptive Kalman Filter," IEEE Trans Automat Contr, pp.175-184, 1970.