A kind of distributed fusion incremental Kalman filter

Guangming Yan, David Tien, Xiaojun Sun

Research output: Book chapter/Published conference paperConference paperpeer-review

1 Citation (Scopus)


The unknown system error is widespread, but it is difficult to be verified or corrected. Furthermore, it also will yield to relatively large filtering errors. As an effective solution, the incremental equation is introduced, which can eliminate these unknown system errors. Meanwhile, the accuracy of state estimators will be improved. Then, a kind of distributed fusion incremental Kalman filter is presented in this paper. It can greatly improve the accuracy of state estimation for the multisensor systems under poor observation condition. The proposed algorithm is easy to be applied in engineering practice because of its simple form and small computational burden so. The simulation results show that it is effective and feasible.
Original languageEnglish
Title of host publicationICSEng 2018 26th international conference on systems engineering
Subtitle of host publicationConference proceedings
Place of PublicationNew Jersey, USA
Number of pages3
ISBN (Electronic)9781538678343
ISBN (Print)9781538678350 (Print on demand)
Publication statusPublished - 2018
Event26th International Conference on Systems Engineering, ICSEng 2018: ICSEng 2018 - University of Technology Sydney, Sydney, Australia
Duration: 18 Dec 201820 Dec 2018
http://www.icseng.com/previous/2018/ (Conference website)
http://www.icseng.com/previous/2018/program.php (Program and papers)


Conference26th International Conference on Systems Engineering, ICSEng 2018
OtherThe conference will provide a high-level forum for scholars, researchers and engineers from all over the world to share their views, research achievements, explore the hot issues and exchange the new experiences and technologies in the fields of Systems Engineering.
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