Optimal attitude determination method in presence of noise and bias on different star sensors

  • Authors

    • Amir Moghtadaei Rad Department of Electrical Engineering,Hashtgerd branch, Islamic azad university,Alborz,Iran
    2014-04-15
    https://doi.org/10.14419/ijet.v3i2.2216

  • There are different attitude determination methods which have been used in satellite and spacecraft by star tracker. Each of these methods have its own advantages and disadvantages depending on their application, stochastic characteristic of noise on sensors (bias or noise), and weight of noise falling on different sensors. The present study has thus explored the major methods from two perspectives: the effect of input noise or bias on each star sensor and the corresponding weight of each noise or bias falling on each sensor. These aspects are compared in each method and the optimal method according to each condition is introduced. N Vector, Triad, Quest, Q method and least square method are the methods studied and simulated in this article. Finally, a comparison is made between the methods and the optimal method is introduced theoretically and practically.

     

    Keywords: Attitude Determination, Celestial Navigation, Triad, Quest, Least Square, Satellite.

  • References

    1. Cole, C. C. (2004). Fast Star Pattern Recognition Using Planar Triangles. AIAA/AAS
    2. Cole, C. L., & Crassidus, J. L. (2004). Fast Star Pattern Recognition Using Spherical Triangles. AIAA/AAS Astrodynamics Specialist Conference and Exhibit. Providence, Rhode Island: AIAA.
    3. Christian Liebe, (2002). Accuracy Performance of Star Trackers A Tutorial. IEEE Transactions on Aerospace and Electronic Systems, 587–599.
    4. R. Thurmond, (2003). “A History of Star Catalogues”,www.rickthurmond.com/History of star catalogues.pdf.
    5. M. A. Samaan, (2003). “Toward Faster and More Accurate Star Sensors using Recursive Centroiding and Star Identification”, Doctoral Dissertation in Aerospace Engineering, Texas A&M University,
    6. Weiss, C. H., Bar-Itzhack, I. Y., & Oshman, Y. (2005). Quaternion Estimation from Vector Observations Using a Matrix Kalmann Filter. AIAA Guidance, Navigation,and Control Conference and Exhibit. San Francisco, CA: AIAA.
    7. Bar-Itzack, Itzhack Y; Harman, Richard R. Optimized TRIAD Algorithm for Attitude Determination. Flight Dynamics Support Branch, Code 553. Greenbelt, MD.
    8. Shuster, M., & Oh, S. (1981). Three-Axis Attitude Determination from Vector Observations. Journal of Guidance and Control, 70–77.
    9. [9] Kara M. Huffman,(2006). “Designing Star Trackers to Meet Microsatellite Requirements “, Mater of Science in Aeronautics and Astronautics Thesis, Massachusetts Institute of technology.
    10. D. Mortari, M. A. Samaan, C. Bruccoleri, J. L. Junkins, (2004). “The Pyramid Star Identification Technique”, Texas A&M University, College Station, Texas,
    11. John L. Crassidis, F. Landis Markley, (2007).Survey of Nonlinear Attitude Estimation Methods, Journal of Guidance, Control, and Dynamics, Vol. 30, No. 1, January–February
    12. Wertz, J. R., (1984). Spacecraft Attitude Determination and Control.Reidel, Dordrecht, the Netherlands.
    13. Shuster, M. D., (1993). “A Survey of Attitude Representations,” The Journal of the Astronautically Sciences, Vol. 41, pp. 439–517.
    14. Wahba, G. (1966). Problem 65-1, a Least Squares Estimate of Satellite Attitude. Society for Industrial and Applied Mathematics, 385–386.

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  • How to Cite

    Moghtadaei Rad, A. (2014). Optimal attitude determination method in presence of noise and bias on different star sensors. International Journal of Engineering & Technology, 3(2), 155-165. https://doi.org/10.14419/ijet.v3i2.2216