Analysis and comparison of nonlinear filtering methods

This paper deals with the state estimation of a strongly nonlinear system. In a noisy state space representation setting, Central Difference Kalman Filter, Ensemble Kalman Filter and Particle Filter are tested on a second order system. The choice of estimators parameters is then discussed, and their behaviour in relation to noise is studied, in order to compare estimation quality according to noise's variance criteria.

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