Abstract
In the paper, we give the numerical simulation of nonlinear filtering problem. We introduce the basic filtering problem and review the reduction from robust Duncan-Mortensen-Zakai equation to Kolmogorov equation firstly. Then the difference scheme of the Kolmogorov equation is given to calculate the nonlinear filtering equation. We derive the result that the solution of the difference scheme convergences pointwise to the solution of the initial-value problem of the Kolmogorov equation. Numerical experiments show that the numerical method can give the exact result.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kalman, R.E., Bucy, R.S.: New results in linear filtering and prediction theory. Trans. ASME Series D, J. Basic Engineering 83(196), 95–108
Kailath, T.: An innovations approach to least-squares estimation, Part I: Linear filtering in additive white noise. IEEE Transactions on Automatic Control 13, 646–655 (1986)
Frost, P.A., Kailath, T.: An innovations approach to least-squares estimation II. IEEE Transactions on Automatic Control 16, 217–226 (1971)
Fujisaki, M., Kallianpur, G., Kunita, H.: Stochastic differential equations for the nonlinear filtering problem. Osaka Journal of Mathematics 2, 19–40 (1972)
Brockett, R.W., Clark, J.M.C.: The geometry of the conditional density functions. In: Jacobs, O.L.R., et al. (eds.) Analysis and Optimization of Stochastic Systems, pp. 299–309. Academic Press, New York (1980)
Brockett, R.W.: Nonlinear systems and nonlinear estimation theory. In: Hazewinkel, M., Williams, J.C. (eds.) The Mathematics of Filtering and Identification and Application, pp. 479–504. Reidel, Dordrecht (1981)
Mittar, S.K.: On the analogy between mathematical problems of nonlinear filtering and quantum physics. Ricerche Automat. 10, 163–216 (1979)
Yau, S.S.-T., Hu, G.-Q.: Classification of finite dimensional estimation algebras of maximal rank with arbitrary state-space dimension and Mitter Conjecture. International Journal of Control 78(10), 689–705 (2005)
Chen, J., Yau, S.S.-T.: Finite dimensional filters with nonlinear drift VI: Linear structure of Ω. Mathematics of Control, Signals and Systems 9, 370–385 (1996)
Yau, S.S.-T., Wu, X., Wong, W.S.: Hessian matrix non-decomposition theorem. Mathematical Research Letter 6, 1–11 (1999)
Yau, S.-T., Yau, S.S.-T.: Existence and uniqueness and decay estimates for the time dependent parabolic equation with application to Duncan-Mortensen-Zakai equation. Asian Journal of Mathematics 2, 1079–1149 (1998)
Yau, S.-T., Yau, S.S.-T.: Real time solution of nonlinear filtering problem without memory I. Mathematical Research Letter 7, 671–693 (2000)
Yau, S.-T., Yau, S.S.-T.: Real time solution of nonlinear filtering problem without memory II (preprint)
Davis, M.H.A.: On a multiplicative functional transformation arising in nonlinear filtering theory. Z. Wahrsch Verw. Gebiete 54, 125–139 (1980)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, Z., Dong, F., Ding, L. (2011). Numerical Simulation of Nonlinear Filtering Problem. In: Lin, S., Huang, X. (eds) Advanced Research on Computer Education, Simulation and Modeling. CESM 2011. Communications in Computer and Information Science, vol 176. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21802-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-21802-6_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21801-9
Online ISBN: 978-3-642-21802-6
eBook Packages: Computer ScienceComputer Science (R0)