Abstract
This paper demonstrates the implementation of an Extended Kalman Filter (EKF) technique as a model-based vehicle state estimator. In this approach, the KF is simplified such that the Kalman gain matrix is not calculated online via the Jacobian and covariance matrices, but using a table of velocity dependent approximating functions, thus reducing the computational effort. Results to date indicate that this is an effective approach, which is of significant potential benefit to the automotive industry.
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