The damped modified iterated Kalman filter for nonlinear discrete time systems

Abstract

The modified iterated Kalman filter, which will be called MIKF for brevity, is derived from the modified Newton method to approximate a maximum likelihood estimate. The MIKF is also obtained by an iteration scheme for the extended kalman filter equations. A convergence analysis of the MIKF is given. By the damping method, we can reduce the total CPU time needed to estimate the state variables or may even obtain a convergent scheme when the MIKF diverges. A numerical example shows the effective convergence behavior of the damped MIKF.