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Check out the Extended Kalman filter for non-linear systems.



Maybe better to check unscented Kalman filter instead, because the extended one is a mathematical horror.


The EKF works by linearizing the process, and suffers on even moderately nonlinear models as a result. It also suffers from the Gaussian assumption. So people switched to unscented (tries to model the underlying probability better) and particle filters (same idea), each giving better accuracy for most all problems. Now plenty of problems are switching to full Bayesian models as the ultimate in accuracy.

So if you like KF, EKF, UKF, be sure to look into this entire chain of accuracy vs computation tradeoff algorithms.




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