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Land Vehicle Navigation with the Integration of GPS and Reduced INS: Performance Improvement with Velocity Aiding

Published online by Cambridge University Press:  01 December 2009

Songlai Han*
Affiliation:
(National University of Defense Technology, China) (The University of New South Wales, Australia)
Jinling Wang
Affiliation:
(The University of New South Wales, Australia)

Abstract

The movement of a land vehicle is constrained because the vehicle always remains on the Earth's surface and only experiences small pitch and roll angles. So the GPS/INS integrated system for land vehicle navigation could be reconfigured to be the integration of GPS and reduced INS to cut down the costs. In a reduced INS, the vertical accelerometer and two horizontal gyros could be omitted from the system. But both theoretical analysis and experimental results show that this configuration may result in the divergence of height solution and large velocity errors. To improve the system performances, precise velocity derived from GPS carrier phase measurements, together with the GPS single point positioning solution, is used to aid the reduced INS. Field test results have demonstrated that first, the aiding from GPS precise velocity overcomes the divergence problem of the integrated height solutions and improves the integrated velocity and secondly the proposed novel integration scheme could achieve comparable navigation accuracy with that from the GPS and full INS integrated system.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2009

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References

REFERENCES

Brandt, A. and Gardner, J. F. (1998). Constrained Navigation Algorithms for Strapdown Inertial Navigation Systems with Reduced Set of Sensors, Proceedings of the American Control Conference, Philadelphia, Pennsylvania, USA, June 24–26, 18481852.Google Scholar
Brown, R. G. and Hwang, P. Y. C. (1997). Introduction to Random Signals and Applied Kalman Filtering (3rd Edition). John Wiley & Sons, Inc.Google Scholar
Graas, F. V. and Soloviev, A. (2004). Precise Velocity Estimation Using a Stand-Alone GPS Receiver, Navigation: Journal of The Institute of Navigation, 51(4), 283292.CrossRefGoogle Scholar
Han, S. and Wang, J. (2008). Monitoring the Degree of Observability in Integrated GPS/INS Systems, International Symposium on GPS/GNSS 2008, Tokyo, Japan, November 11–14, 414421.Google Scholar
Niu, X., Nasser, S., Goodall, C. and El-Sheimy, N. (2007). A Universal Approach for Processing any MEMS Inertial Sensor Configuration for Land-Vehicle Navigation, The Journal of Navigation, 60, 233245.CrossRefGoogle Scholar
Phuyal, B. (2004). An Experiment for a 2-D and 3-D GPS/INS Configuration for Land Vehicle Applications, Proceedings of the IEEE Position Location and Navigation Symposium (PLANS 2004), Monterey, California, USA, April 26–29, 148152.Google Scholar
Savage, P. G. (2000), Strapdown analytics, Strapdown Associates, Inc.Google Scholar
Yates, R. D. and Goodman, D. J. (1998). Probability and Stochastic Processes—A Friendly Introduction for Electrical and Computer Engineers. John Wiley & Sons, Inc.Google Scholar