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  • 1. Kalman Filter Tutorial (Cont'd...)

    1.6 Conclusion

    In this article, We revisited the Kalman filter estimation. We describe the assumptions, method and algorithm of the recursive discrete Kalman filte. Also we lucidly describe the derivation of the algorithm step by step. Few important properties are also illustrated. The algorithm has been implemented to estimate position, velocity and acceleration for a particle moving in three dimensional space. We assume that only position measurement is available from the sensor. Simulation results shows the error of the estimator. We carried out few tests to determine the correctness of the process model.

    Reference

    S. Julier, J. Uhlmann and H. F. Durrant-Whyte, "A new method for the nonlinear transformation of means and covariances in filters and estimators," IEEE Trans. Autom. Control., vol. 45, no. 3, Mar. 2000.

    M. S. Arulampalam, S. Maskell, N. Gordon and T. Clapp, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Trans. Signal Process., vol. 50, no. 2, Feb. 2002.

    R. G. Brown, "Introduction to random signal analysis and Kalman filtering," New York, John Wiley & Sons, Inc., 1983.

    E. Brookner, "Tracking and Kalman filtering made easy, " New York, John Wiley & Sons, Inc., 1998.

    D. Simon, "Optimal state estimation, " New Jersey, John Wiley & Sons, Inc., 2006.

    Y. Bar-Shalom, X. R. Li and T. Kirubarajan, "Estimation with applications to tracking and navigation," New York, John Wiley & Sons, Inc., 2001.

    M. S. Grewal and A. P. Andrews, "Kalman filtering," New Jersey, John Wiley & Sons, Inc., 2008.

    B. D. O. Anderson and J. B. Moore, "Optimal filtering," New Jersey, Prentice-Hall, Inc., 1979.

    D. Simon, "Kalman filtering with state constraints: a survey of linear and nonlinear algorithms," IET Control Theory Appl., vol. 4, Iss. 8, pp. 1303-1308, May 2009.

    S. A. Elgamel and J. Soraghan, "Target tracking enhancement using a Kalman filter in the presence of interference," IEEE IGARSS, vol. 3, July 2009.

    R. A. Singer, "Estimating optimal tracking filter performance for manned maneuvering targets," IEEE Trans. Aerosp. Electron. Syst., vol. 6, no. 4, July 1970.

    R. A. Singer and R. G. Sea, "Increasing the computational efficiency of discrete Kalman filters," IEEE Trans. Autom. Control, June 1971.

    R. F. Ohap and A. R. Stubberud, "A technique for estimating the state of a nonlinear system," IEEE Trans. Autom. Control, vol. 10, Iss. 2, Apr. 1965.

    N. Tanabe, T. Furukawa and S. Tsujii, "Fast noise suppression with Kalman filter theory," IEEE ISUC, Dec. 2008.



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