Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-09T13:25:21.718Z Has data issue: false hasContentIssue false
  • English
  • Français

A Novel Initial Alignment Scheme for Low-Cost INS Aided by GPS for Land Vehicle Applications

Published online by Cambridge University Press:  13 September 2010

Songlai Han  and
Jinling Wang
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)
*
(Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper proposes a novel mechanism for the initial alignment of low-cost INS aided by GPS. For low-cost INS, the initial alignment is still a challenging issue because of the high noises from low-cost inertial sensors. In this paper, a two-stage Kalman Filtering mechanism is proposed for the initial alignment of low-cost INS. The first stage is designed for the coarse alignment. To solve the problems encountered by the general coarse alignment approach, an INS error dynamic accounting for unknown initial heading error is developed, and the corresponding observation equation, taking into account the unknown heading error, is also developed. The second stage is designed for the fine alignment, where the classical INS error dynamics based on small attitude error is used. Experimental results indicate that the proposed alignment approach can complete the initial alignment more quickly and more accurately compared with the conventional approach.

Keywords

Low-Cost INSInitial AlignmentGPSLand Vehicle
Type
Research Article
Information
The Journal of Navigation , Volume 63 , Issue 4 , October 2010 , pp. 663 - 680
Copyright
Copyright © The Royal Institute of Navigation 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Baziw, J., and Leondes, C. T. (1972a). In-Flight Alignment and Calibration of Inertial Measurement Units-Part I: General Formulation, IEEE Transactions on AES, 8(4), 439–449.Google Scholar
Baziw, J., and Leondes, C. T. (1972b). In-Flight Alignment and Calibration of Inertial Measurement Units-Part II: Experimental Results, IEEE Transactions on AES, 8(4), 450–465.Google Scholar
Bar-Itzhack, I. Y., and Porat, B. (1980). Azimuth Observability Enhancement During Inertial Navigation System In-Flight Alignment, Journal of Guidance and Control, 3(4), 337–344.CrossRefGoogle Scholar
Benson, D. O., (1975). A Comparison of Two Approaches to Pure-Inertial and Doppler-Inertial Error Analysis, IEEE Transactions on AES, 11(4), 447–455.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
Dmitriyev, S. P., Stepanov, O. A., and Shepel, S. V., (1997). Nonlinear Filtering Methods Application in INS Alignment, IEEE Transactions on AES, 33(4), 260–272.Google Scholar
Goshen-Meskin, D., and Bar-Itzhack, I. Y. (1992) Unified approach to inertial navigation system error modeling. Journal of Guidance, Control, and Dynamics, 15(3): 648–653.CrossRefGoogle Scholar
Greenspan, R. L., (1995). Inertial Navigation Technology from 1970–1995, Navigation: Journal of The Institute of Navigation, 42(4), 165–185.CrossRefGoogle Scholar
Groves, P. D., (2008). Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems. Artech House.Google Scholar
Han, S. and Wang, J. (2008) Monitoring degree of observability in GPS/INS integration. Int. Symp. on GPS/GNSS, Yokohama, Japan, 25–28 November, 414–421.Google Scholar
Kelley, R., Katz, I., and Bedoya, C. (1990). Design, Development and Evaluation of an ADA Coded INS/GPS Open Loop Kalman Filter, Proceedings of the IEEE 1990 National Aerospace and Electronics Conference, Vol. 1, 382–388.Google Scholar
Kong, X., Nebot, E. M., and Durrant-Whyte, H., (1999). Development of a non-linear psi-angle model for large misalignment errors and its application in INS alignment and calibration, Proceedings of the 1999 IEEE International Conference on Robotics and Automation, Detroit, Michigan, May, 1430–1435.Google Scholar
Lee, H. Y., Wang, J., Rizos, C., Grejner-Brzezinska, D. and Toth, C. (2002) GPS/pseudolite/INS: Concept and first tests. GPS Solutions, 6(1–2), 34–46.CrossRefGoogle Scholar
Shin, E., and El-Sheimy, N., (2004). An unscented Kalman filter for in-motion alignment of low-cost IMUs, Position Location and Navigation Symposium, Monterey, CA, Aprial, 273–279.Google Scholar
Martin, M. K., and Detterich, B. C., (1997). C-MIGITSTM II Design and Performance. Proceedings of the Satellite Division of the Institute of Navigation 10th International Technical Meeting: ION GPS-97, September 16–19.Google Scholar
Pham, T. M. (1992). Kalman Filter Mechanization for INS Airstart, IEEE AES Systems Magazine, 7(4), 3–11.CrossRefGoogle Scholar
Rogers, R. M., (1997). IMU In-Motion Alignment without Benefit of Attitude Initialization, Navigation: Journal of The Institute of Navigation, 44(4), 301–311.CrossRefGoogle Scholar
Savage, P. G., (2000). Strapdown Analytics. Strapdown Associates, Inc.Google Scholar
Wang, J., Lee, H. K., Hewitson, S. and Hyung-Keun, Lee (2003) Influence of Dynamics and Trajectory on Integrated GPS/INS Navigation Performance, Journal of Global Positioning Systems, 2(2), 109–116, (http://www.cpgps.org/journal.php)CrossRefGoogle Scholar