Multisensor data synthesis using federated form of unscented Kalman filtering

Jamshaid Ali; Jiancheng Fang

doi:10.1109/ICIT.2005.1600694

Multisensor data synthesis using federated form of unscented Kalman filtering

Jamshaid Ali^*
, Jiancheng Fang

^*Corresponding author for this work

School of Instrumentation and Optoelectronic Engineering

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Scopus citations

Abstract

In this paper, a decentralized unscented Kalman Filter (UKF) in federated configuration is developed for multisensor navigation data fusion. The UKF is a nonlinear, distribution approximation method that uses a finite number of points to propagate the state's probability distribution through the system's nonlinear dynamics. In multisensor data fusion application, the configuration features of the federated unscented Kalman filter (FUKF) are investigated. To elaborate the concept of this filter structure, a case study of the strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) and global positioning system (GPS) is presented. Simulation results demonstrate the validity of the proposed filter configuration.

Original language	English
Title of host publication	2005 IEEE International Conference on Industrial Technology, ICIT 2005
Pages	524-529
Number of pages	6
DOIs	https://doi.org/10.1109/ICIT.2005.1600694
State	Published - 2005
Event	2005 IEEE International Conference on Industrial Technology, ICIT 2005 - Hong Kong, Hong Kong SAR Duration: 14 Dec 2005 → 17 Dec 2005

Publication series

Name	Proceedings of the IEEE International Conference on Industrial Technology
Volume	2005

Conference

Conference	2005 IEEE International Conference on Industrial Technology, ICIT 2005
Country/Territory	Hong Kong SAR
City	Hong Kong
Period	14/12/05 → 17/12/05

Access to Document

10.1109/ICIT.2005.1600694

Cite this

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title = "Multisensor data synthesis using federated form of unscented Kalman filtering",

abstract = "In this paper, a decentralized unscented Kalman Filter (UKF) in federated configuration is developed for multisensor navigation data fusion. The UKF is a nonlinear, distribution approximation method that uses a finite number of points to propagate the state's probability distribution through the system's nonlinear dynamics. In multisensor data fusion application, the configuration features of the federated unscented Kalman filter (FUKF) are investigated. To elaborate the concept of this filter structure, a case study of the strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) and global positioning system (GPS) is presented. Simulation results demonstrate the validity of the proposed filter configuration.",

author = "Jamshaid Ali and Jiancheng Fang",

year = "2005",

doi = "10.1109/ICIT.2005.1600694",

language = "英语",

isbn = "0780394844",

series = "Proceedings of the IEEE International Conference on Industrial Technology",

pages = "524--529",

booktitle = "2005 IEEE International Conference on Industrial Technology, ICIT 2005",

note = "2005 IEEE International Conference on Industrial Technology, ICIT 2005 ; Conference date: 14-12-2005 Through 17-12-2005",

}

Ali, J & Fang, J 2005, Multisensor data synthesis using federated form of unscented Kalman filtering. in 2005 IEEE International Conference on Industrial Technology, ICIT 2005., 1600694, Proceedings of the IEEE International Conference on Industrial Technology, vol. 2005, pp. 524-529, 2005 IEEE International Conference on Industrial Technology, ICIT 2005, Hong Kong, Hong Kong SAR, 14/12/05. https://doi.org/10.1109/ICIT.2005.1600694

Multisensor data synthesis using federated form of unscented Kalman filtering. / Ali, Jamshaid; Fang, Jiancheng.
2005 IEEE International Conference on Industrial Technology, ICIT 2005. 2005. p. 524-529 1600694 (Proceedings of the IEEE International Conference on Industrial Technology; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Fang, Jiancheng

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N2 - In this paper, a decentralized unscented Kalman Filter (UKF) in federated configuration is developed for multisensor navigation data fusion. The UKF is a nonlinear, distribution approximation method that uses a finite number of points to propagate the state's probability distribution through the system's nonlinear dynamics. In multisensor data fusion application, the configuration features of the federated unscented Kalman filter (FUKF) are investigated. To elaborate the concept of this filter structure, a case study of the strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) and global positioning system (GPS) is presented. Simulation results demonstrate the validity of the proposed filter configuration.

AB - In this paper, a decentralized unscented Kalman Filter (UKF) in federated configuration is developed for multisensor navigation data fusion. The UKF is a nonlinear, distribution approximation method that uses a finite number of points to propagate the state's probability distribution through the system's nonlinear dynamics. In multisensor data fusion application, the configuration features of the federated unscented Kalman filter (FUKF) are investigated. To elaborate the concept of this filter structure, a case study of the strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) and global positioning system (GPS) is presented. Simulation results demonstrate the validity of the proposed filter configuration.

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U2 - 10.1109/ICIT.2005.1600694

DO - 10.1109/ICIT.2005.1600694

M3 - 会议稿件

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SN - 0780394844

SN - 9780780394841

T3 - Proceedings of the IEEE International Conference on Industrial Technology

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BT - 2005 IEEE International Conference on Industrial Technology, ICIT 2005

T2 - 2005 IEEE International Conference on Industrial Technology, ICIT 2005

Y2 - 14 December 2005 through 17 December 2005

ER -

Multisensor data synthesis using federated form of unscented Kalman filtering

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