A novel approach of noise statistics estimate using H ∞ filter in target tracking-Reference-Cited by-同舟云学术

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A novel approach of noise statistics estimate using H ∞ filter in target tracking

Published:2016-05 Issue:5 Volume:17 Page:449-457
ISSN:2095-9184
Container-title:Frontiers of Information Technology & Electronic Engineering
language:en
Short-container-title:Frontiers Inf Technol Electronic Eng

Author:

Wang Xie,Liu Mei-qin,Fan Zhen,Zhang Sen-lin

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Specialized Research Fund for the Doctoral Program of Higher Education of China

Open Fund for the Aircraft Marine Measurement and Control Joint Laboratory, China

Aerospace Science Foundation of China

Publisher

Zhejiang University Press

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing

Link

http://link.springer.com/article/10.1631/FITEE.1500262/fulltext.html

Reference27 articles.

1. Alouani, A.T., Blair, W.D., 1993. Use of a kinematic constraint in tracking constant speed, maneuvering targets. IEEE Trans. Autom. Contr., 38(7):1107–1111. http://dx.doi.org/10.1109/9.231465

2. Alspach, D.L., Scharf, L.L., Abiri, A., 1974. A Bayesian solution to the problem of state estimation in an unknown noise environment. Int. J. Contr., 19(2):265–287. http://dx.doi.org/10.1080/00207177408932628

3. Assa, A., Janabi-Sharifi, F., 2014. A robust vision-based sensor fusion approach for real-time pose estimation. IEEE Trans. Cybern., 44(2):217–227. http://dx.doi.org/10.1109/TCYB.2013.2252339

4. Banavar, R.N., 1992. A Game Theoretic Approach to Linear Dynamic Estimation. PhD Thesis, Texas University, Austin, USA.

5. Bavdekar, V.A., Deshpande, A.P., Patwardhan, S.C., 2011. Identification of process and measurement noise covariance for state and parameter estimation using extended Kalman filter. J. Process Contr., 21(4):585–601. http://dx.doi.org/10.1016/j.jprocont.2011.01.001

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