Machine learningNonlinear Estimation
Extended Kalman Filter
The Extended Kalman Filter (EKF) is the nonlinear generalization of the Kalman Filter, extending the linear state estimation algorithm to nonlinear systems through local linearization. Developed by Bucy in the early 1960s, the EKF has become the workhorse for state estimation in nonlinear systems across robotics, aerospace, and navigation, enabling real-time processing of noisy measurements from nonlinear sensors and dynamics.
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Sources
- Bucy, R. S. (1961). A linear approximation to the solution of nonlinear filtering equations. Technical Report No. 32-486, Jet Propulsion Laboratory. link ↗
- Bar-Shalom, Y., Li, X. R., & Kirubarajan, T. (2001). Estimation with Applications to Tracking and Navigation. Wiley-Interscience. DOI: 10.1002/0471221546 ↗
- Welch, G., & Bishop, G. (2006). An Introduction to the Kalman Filter. UNC-CH Technical Report. link ↗