Interacting multiple model algorithm based on H_∞ filter

In practice, the noise statistics are usually unknown or not perfectly known. To deal with the estimation problem in linear discrete-time systems with Markov jump parameters, where the measurement noise covariance is unknown, a approach was presented. This approach was based on the interacting multiple model (IMM) framework. A H_∞ filter was employed to construct a noise statistics estimator to obtain the information which was necessary for the IMM algorithm. In the proposed approach, the noise statistics loss problem was solved while the merits of IMM algorithm was reserved. The effectiveness of the proposed approach was demonstrated in comparison with single-model H_∞ filter through Monte Carlo simulation for maneuvering target tracking.