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Integration of Star and Inertial Sensors for Spacecraft Attitude Determination

Published online by Cambridge University Press:  27 June 2017

Kedong Wang ,
Tongqian Zhu ,
Yujie Qin ,
Chao Zhang  and
Yong Li
Kedong Wang*
Affiliation:
(School of Astronautics, Beihang University, Beijing 100191, China)
Tongqian Zhu
Affiliation:
(School of Astronautics, Beihang University, Beijing 100191, China)
Yujie Qin
Affiliation:
(School of Astronautics, Beihang University, Beijing 100191, China)
Chao Zhang
Affiliation:
(School of Astronautics, Beihang University, Beijing 100191, China)
Yong Li
Affiliation:
(School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, Australia)
*
(E-mail: [email protected])
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Abstract

A new integration of the acquisition and tracking modes is proposed for the integration of a Celestial Navigation System (CNS) and a Strapdown Inertial Navigation System (SINS). After the integration converges in the acquisition mode, it switches to the tracking mode. In the tracking mode, star pattern recognition is unnecessary and the integration is implemented in a cascaded filter scheme. A pre-filter is designed for each identified star and the output of the pre-filter is fused with the attitude of the SINS in the cascaded navigation filter. Both the pre-filter and the navigation filter are designed in detail. The measurements of the pre-filter are the positions on the image plane of one identified star. Both the starlight direction and its error are estimated in the pre-filter. The estimated starlight directions of all identified stars are the measurements of the navigation filter. The simulation results show that both the reliability and accuracy of the integration are improved and the integration is effective when only one star is identified in a period.

Keywords

Star sensorCelestial navigation systemInertial navigation systemKalman filter
Type
Research Article
Information
The Journal of Navigation , Volume 70 , Issue 6 , November 2017 , pp. 1335 - 1348
Copyright
Copyright © The Royal Institute of Navigation 2017 

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References

REFERENCES

Ali, J. and Fang, J. C. (2006). SINS/ANS integration for augmented performance navigation solution using unscented Kalman filtering. Aerospace Science and Technology, 10(3), 233–238.Google Scholar
Bar-Itzhach, I. Y., Serfaty, D. and Vitek, Y. (1982). Doppler-aided low-accuracy strapdown inertial navigation system. Journal of Guidance, Control, and Dynamics, 5(3), 236–242.CrossRefGoogle Scholar
Batista, P., Silvestre, C. and Oliveira, P. (2011). Vector-based attitude filter for space navigation. Journal of Intelligent and Robotic Systems: Theory and Applications, 64(2), 221–243.Google Scholar
Hablani, H. B. (2009). Autonomous inertial relative navigation with sight-line-stabilized integrated sensors for spacecraft rendezvous. Journal of Guidance, Control and Dynamics, 32(1), 172–183.Google Scholar
Harold, D. B. (1964). A passive system for determining the attitude of a satellite. AIAA Journal, 2(7), 1350–1351.Google Scholar
He, Z., Wang, X. and Fang, J. (2014). An innovative high-precision SINS/CNS deep integrated navigation scheme for the Mars rover. Aerospace Science and Technology, 39, 559–566.Google Scholar
Ho, K. (2012). A survey of algorithms for star identification with low-cost star trackers. Acta Astronautica, 73, 156–163.Google Scholar
Huffman, K. M. (2006). Designing star trackers to meet micro-satellite requirements. Massachusetts Institutes of Technology.Google Scholar
Johnson, W. M. and Phillips, R. E. (2001). Steller/inertial (EBCCD/MEMS) attitude measurement & control of small satellites. Proceedings of AIAA Space Conference and Exposition, Albuquerque, NM, USA, August 28–30.Google Scholar
Ju, G. and Junkins, J. L. (2003). Overview of star tracker technology and its trends in research and development. Advances in the Astronautical Sciences, 115, 461–477.Google Scholar
Lashley, M., Bevly, D. M. and Hung, J. Y. (2009). Performance analysis of vector tracking algorithms for weak GPS signals in high dynamics. IEEE Journal on Selected Topics in Signal Processing, 3(4), 661–673.Google Scholar
Levine, S., Dennis, R. and Bachman, K. L. (1990). Strapdown Astro-inertial navigation utilizing the optical wide-angle lens startracker. Navigation: Journal of the Institute of Navigation, 37(4), 347–362.CrossRefGoogle Scholar
Liebe, C. C. (1995). Star trackers for attitude determination. IEEE Aerospace and Electronic Systems Magazine, 10(6), 10–16.Google Scholar
Liebe, C. C. (2002). Accuracy Performance of Star Trackers: A Tutorial. IEEE Transactions on Aerospace and Electronic Systems, 38(2), 587–599.Google Scholar
Liu, B., Wang, K. and Zhang, C. (2011). Star pattern recognition algorithm aided by inertial information. Proceedings of SPIE, 8196, Beijing, China.Google Scholar
Ning, X., Gui, M., Xu, Y., Bai, X. and Fang, J. (2016). INS/VNS/CNS integrated navigation method for planetary rovers. Aerospace Science and Technology, 48, 102–114.Google Scholar
Percival, J. W., Nordsieck, K. H. and Jaehnig, K. P. (2008). The ST5000: a high-precision star tracker and attitude determination system. Proceedings of SPIE, 7010, 70104H-1–70104H-6.CrossRefGoogle Scholar
Rad, A. M., Nobari, J. H. and Nikkhah, A. A. (2014). Optimal attitude and position determination by integration of INS, star tracker, and horizon sensor. IEEE Aerospace and Electronic Systems Magazine, 29(4), 20–33.Google Scholar
Scholl, M. S. (1995). Star-field identification for autonomous attitude determination. Journal of Guidance, Control and Dynamics, 18(1), 61–65.Google Scholar
Shuster, M. D. and Oh, S. D. (1981). Three-axis attitude determination from vector observations. Journal of Guidance and Control, 4(1), 70–77.Google Scholar
Silani, E. and Lovera, M. (2006). Star identification algorithm: novel approach & comparison study. IEEE Transactions on Aerospace and Electronic Systems, 42(4), 1275–1288.Google Scholar
Sun, T., Xing, F., You, Z. and Li, B. (2014). Deep coupling of star tracker and MEMS-gyro data under highly dynamic and long exposure conditions. Measurement Science and Technology, 25(8), 1–15.Google Scholar
Wang, H., Zhou, W. and Cheng, X. (2012). Image smearing modeling and verification for strap-down star sensor. Chinese Journal of Aeronautics, 25(1), 115–123.Google Scholar
Wang, K., Zhang, C. and Yong, L. (2014). A new restoration algorithm for the smeared image of a SINS-aided star sensor. Journal of Navigation, 67, 881–898.CrossRefGoogle Scholar
Wang, X., Guan, X., Fang, J. and Li, H. (2015). A high accuracy multiplex two-position alignment method based on SINS with the aid of star sensor. Aerospace Science and Technology, 42, 66–73.Google Scholar
Wu, X. and Wang, X. (2011). A SINS/CNS deep integrated navigation method based on mathematical horizon reference. Aircraft Engineering and Aerospace Technology, 83(1), 26–34.Google Scholar
Wu, X. and Wang, X. (2011). Multiple blur of star image and the restoration under dynamic conditions. Acta Astronautica, 68(11-12), 1903–1913.Google Scholar
Xu, F. and Fang, J. (2008). Velocity and position error compensation using strapdown inertial navigation system/celestial navigation system integration based on ensemble neural network. Aerospace Science and Technology, 12(4), 302–307.Google Scholar
Yang, Y. (2012). Spacecraft attitude determination and control: quaternion based method. Annual Reviews in Control, 36, 198–219.Google Scholar