Modified extended Kalman filtering and a real-time parallel algorithm for system parameter identification

摘要

A modification of the extended Kalman filter (EKF) algorithm, which is called MEKF for short, it introduced. The modification is achieved by an improved linearization procedure. For this purpose, a parallel computational scheme is recommended, and it has immediate applications to identifying unknown system parameters of time-varying, linear, stochastic state-space models in real time. It should be noted that just like the EKF, the MEKF is also ad hoc in the sense that it is a real-time approximation method. Numerical examples with computer simulation are included to demonstrate the effectiveness of this procedure as compared to the EKF algorithm.