Derivation of Extended (Nonlinear) Kalman Filter From Scratch with Python Codes – PART I – MATH
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In this control theory and estimation tutorial, we explain how to derive the extended (nolinear) Kalman filter that can be used for the state-estimation of nonlinear dynamical systems. We explain how to linearize the state and output equations and how to compute the estimates and covariance matrices. This is the first part of the tutorial that mainly explains mathematical derivations. In the second part of the tutorial, we provide an example together with Python codes.
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