Fusion for a class of Markov switching system with delayed mode measurements

With the development of sensors and requirement for better system performance, an information fusion problem for a class of Markov switching system with delayed mode measurements is put forward. What´s more, when mode measurement is one-step delayed relative to state measurement, this kind of fusion problem is changed into a generalized filtering problem for a common Markov switching system through state-augmentation approach. This algorithm (mode-measurement-enhanced interacting multiple model generalized filtering algorithm, namely mme-IMM-gfa) is derived by Bayes theory, and is illustrated via a maneuvering target tracking simulation example.