Innovation filter and its application to the IMM algorithm using Zhou model

The Interacting Multiple Model (IMM) algorithm is now a more efficient algorithm for tracking targets. But the weight probabilities of the algorithm are more sensitive to the measurement noises. In this paper, we introduce an Innovation Filter (IF) to the algorithm to overcome this shortcoming. The inherent mechanism between IF and IMM algorithm is revealed from theoretical analysis and verified by Monte Carlo simulations. It is different from the Blom's IMM algorithm, we use Zhou model instead of the CA model. Zhou model is much more efficient for tracking the high maneuvering targets. However, while the targets moving with constant velocity, it will lose more accuracy. This paper shows that the new method makes the two approaches, the IMM algorithm and Zhou model, more efficient and perfect.