An interacting multiple model algorithm with a switching Markov chain
A Markov chain plays an important role in an interacting multiple model algorithm which has been shown to be effective for target tracking systems. Such systems are described by a mixing of continuous states and discrete modes. The switching between system modes is governed by a Markov chain. In real world applications, this Markov chain may change or needs to be changed. Therefore, one may be concerned about a target tracking algorithm associated to the switching of a Markov chain. This paper concentrates on fault-tolerant algorithm design and algorithm analysis of interacting multiple model estimation with the switching of a Markov chain. Monte Carlo simulations are carried out and several conclusions are given.
scientific article; zbMATH DE number 1042727