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Lyapunov Stability Analysis of an Orbit Determination Problem

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Abstract

Statistical orbit determination is an important part of tracking satellites and predicting their future location. This is accomplished by processing the raw observation data from ground stations tracking satellites in orbit and estimating the location of these satellites. Kalman filter theory is a popular statistical process but it is not commonly used for satellite orbit determination because it exhibits poor stability characteristics in this application. In particular, an Extended Kalman Filter (EKF) is needed for this application because the orbit determination problem is a nonlinear one. The EKF does not lend itself well to the traditional eigenvalue stability analysis, which is applicable for linear, time-invariant systems. If the stability characteristics of the EKF used for the orbit determination problem were better understood, it could become useful for these applications. A stability analysis concept which has received much attention is Lyapunov’s stability theory. The focus of this paper is to apply the second method of Lyapunov (or the direct method) to evaluate the stability characteristics of an EKF estimating a satellite’s orbit using simulated radar data from ground tracking stations at Mahe Island and Thule. Specifically, a Lyapunov function is used to analyze the stability characteristics of that EKF while selecting the weighting matrices of the filter for the satellite orbit determination problem.

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References

  1. LARSON, W., and WERTZ, J. Space Mission Analysis and Design, 1st ed., Kluwer Academic Publishers, Dordrecht, the Netherlands, 1992, pp. 579–599.

    Book  Google Scholar 

  2. VALLADO, D. A. Fundamentals of Astrodynamics and Applications, McGraw-Hill, New York, 1997, pp. 649–738.

    Google Scholar 

  3. BELLMAN, R., and COOKE, K. Differential-Difference Equations, Academic Press, New York, 1963, pp. 111–187.

    MATH  Google Scholar 

  4. MOORE, J., and ANDERSON, B. “Coping with Singular Transition Matrices in Estimation and Control Stability Theory,” International Journal Control, 1980, pp. 571–586.

  5. SONG, T., and SPEYER, J. “A Stochastic Analysis of a Modified Gain Extended Kalman Filter with Applications to Estimation and Bearing Only Measurement,” IEEE Transactions on Automatic Control, Vol. AC-30, No. 10, 1985, pp. 940–949.

    Article  Google Scholar 

  6. SONG, T., and SPEYER, J. “The Modified Gain Extended Kalman Filter and Parameter Identification in Linear Systems,” Automatica, Vol. 22, No. 1, 1986, pp. 59–75.

    Article  Google Scholar 

  7. GELB, A., KASPER, J., NASH, R., PRICE, C., and SUTHERLAND, A. Applied Optimal Estimation, The Analytic Sciences Coorporation, Cambridge, Massachusetts, 1974.

    Google Scholar 

  8. BATE, R., MUELLER, D., and WHITE, J. Fundamentals of Astrodynamics, Dover Publications, New York, 1971, pp. 385–419.

    Google Scholar 

  9. SELLERS, J. Understanding Space, An Introduction to Astronautics, McGraw-Hill, New York, 1994, pp. 246–267.

    Google Scholar 

  10. BERTRAM, J. E., and SARACHIK, P. E. “Stability of Circuits with Randomly Time-Varying Parameters,” IEEE Transactions on Circuit Theory, May 1959, pp. 260–270.

  11. MAYBECK, P. S. Stochastic Models, Estimation, and Control, Vol 3, Academic Press, New York, 1982, pp. 45–121.

    MATH  Google Scholar 

  12. ANDERSON, B., and MOORE, J. Optimal Filtering, Prentice-Hall, Englewood Cliffs, 1979, pp. 97–131.

    MATH  Google Scholar 

  13. D’AZZO, R. S., and HOUPIS, C. H. Linear Control System Analysis and Design, McGraw Hill, New York, 1975, pp. 509–519.

    MATH  Google Scholar 

  14. LUENBERGER, D. “An Introduction to Observers,” IEEE Transactions on Automatic Control, Vol. AC-16, No. 6, 1971, pp. 596–602.

    Article  MathSciNet  Google Scholar 

  15. ROUCHE, N., HABETS, P., and LALOY, M. “Stability Theory by Liapunov’s Direct Method,” Springer-Verlag, Paris, 1977, pp. 1–89.

    Book  Google Scholar 

  16. MAYBECK, P. S. Stochastic Models, Estimation, and Control, Vol. 1, Academic Press, New York, 1982, pp. 133–195.

    MATH  Google Scholar 

  17. SAFONOV, M., and ATHANS, M. “Robustness and Computational Aspects of Nonlinear Stochastic Estimators and Regulators,” IEEE Transactions Automatic Control, Vol. AC-23, No. 4, 1978, pp. 717–725.

    Article  Google Scholar 

  18. VERGEZ, P. “Closed-Loop System Analysis Using Lyapunov Stability Theory,” Ph.D. Dissertation, University of Texas at Austin, Austin, Texas, May 1987.

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Vergez, P.L. Lyapunov Stability Analysis of an Orbit Determination Problem. J of Astronaut Sci 45, 233–245 (1997). https://doi.org/10.1007/BF03546378

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  • DOI: https://doi.org/10.1007/BF03546378

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