Title :
Estimation of Markov Jump systems with mode observation one-step lagged to state measurement
Author :
Yan Liang ; Zengfu Wang ; Yongmei Cheng ; Quan Pan
Author_Institution :
Northwestern Polytech. Univ., Xi´an
Abstract :
The estimation of Markov jump systems (MJS) is widely used in target tracking, fault detection, signal processing and digital communications. However, the above researches all assume that state measurement and additional mode observation are synchronous which means both state measurement and mode observation at each sampling time arrive at the fusion centre at the same time. The problem of estimation of MJS that mode observation is one-step lagged to its corresponding state measurement is considered. Along state-augmentation approach and the derivation of image-enhanced interacting multiple model (IE-IMM), a new generic estimation algorithm is proposed. It is shown by simulation result that the proposed algorithm is effective.
Keywords :
Markov processes; estimation theory; Markov jump system estimation; generic estimation algorithm; image-enhanced interacting multiple model; mode observation one-step lagged; state measurement; state-augmentation approach; Digital communication; Digital signal processing; Equations; Fault detection; Image sensors; Signal processing algorithms; Smoothing methods; State estimation; Target tracking; Time measurement; Asynchronous fusion; IE-IMM; Markov Jump system; Target tracking;
Conference_Titel :
Information Fusion, 2007 10th International Conference on
Conference_Location :
Quebec, Que.
Print_ISBN :
978-0-662-45804-3
Electronic_ISBN :
978-0-662-45804-3
DOI :
10.1109/ICIF.2007.4408180