Journal of Applied Sciences1812-56541812-5662Asian Network for Scientific Information10.3923/jas.2009.4195.4205ChouraquiS.BenyettouM.122009924This study preliminarily investigates the numerical application of both Extended Kalman Filter (EKF) (which has traditionally been used for non linear estimation) and a relatively new filter, Unscented Kalman Filter (UKF) to the nonlinear estimation problem. The new method can be applied to nonlinear systems without the linearization process necessary for the EKF and it does not demand a Gaussian distribution of noise and what's more, its ease of implementation and more accurate estimation features enables it to demonstrate its good performance. Present experimental results and analysis indicate that unscented Kalman filtering UKF have shown better performances in presence of the severe nonlinearity in state equations.]]>Anderson, A.D., J.J. Sellers and Y. Hashida,2004Chowdhary, G. and R. Jategaonkar,2006Costa, P.J.,1994Hashida, Y.,2004Joseph, J. and L. Viola Jr.2003Julier, S. and J.K. Uhlmann,1994Julier, S., J. Uhlmann and H.F. Durant-Whyte,1995Julier, S.J. and J.K. Uhlmann,1997Julier, S., J. Uhlmann and H.F. Durrant-Whyte,2000Kandepu, R., L. Imsland and B.A. Foss,2008Kushner, H.J. and A.S. Budhiraja, 2000Li, P. and T. Zhang,2002Martin, R.,2001Matthew, C.C., J. Hale, P. Vergez, M.J. Meerman and Y. Hashida,2004Van der Merwe, R., E. Wan and S.J. Julier,2004Viéville, T., E. Clergue and P.E.D.S. Facao,1993Wan, E.A., R. van der Merwe and A.T. Nelson,2000Akin, B., U. Orguner and A. Ersak,2003