The iterated Kalman filter update as a Gauss-Newton method
Abstract
We show that the iterated Kalman filter (IKF) update is an application of
the Gauss-Newton method for approximating a maximum likelihood estimate.
We also present an example in which the iterated
Kalman filter update and maximum likelihood estimate show
correct convergence behavior as the observation becomes more accurate,
whereas the extended Kalman filter update does not.
