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Technical Briefs

Simplified Federated Filtering Algorithm With Different States in Local Filters

[+] Author and Article Information
Guoliang Liu

Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, Chinaliu88@hit.edu.cn

Jian Xie

Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, Chinaxjian@hit.edu.cn

Shizuo Yan

Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, Chinashizuoyan@hit.edu.cn

Wenyi Qiang

Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, Chinawyqiang@hit.edu.cn

J. Dyn. Sys., Meas., Control 133(1), 014507 (Dec 22, 2010) (4 pages) doi:10.1115/1.4002071 History: Received April 24, 2008; Revised June 03, 2010; Published December 22, 2010; Online December 22, 2010

In this paper, to reduce the computation load of federated Kalman filters, a simplified federated filtering algorithm for integrated navigation systems is presented. It has been known that the per-cycle computation load grows roughly in proportion to the number of states and measurements for a single centralized Kalman filter. Hence, the states that have poor estimation accuracies are removed from local filters, so that the per-cycle computation load is reduced accordingly. Local filters and master filter of the federated Kalman filter may have different states, so the transition matrices are required to combine the outputs from the local filters and the master filter properly and to reset the global solution into the local filters and the master filter correctly. An experiment demonstrates that the proposed algorithm effectively reduces the computation load, compared with the standard federated Kalman filtering algorithm.

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Figures

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Figure 1

The federated Kalman filter designed in this paper

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Figure 2

The initial longitude data

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Figure 3

The initial east velocity data

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Figure 4

The longitude when only one LF works

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Figure 5

The east velocity when only one LF works

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Figure 6

The longitude outputs of federated filter

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Figure 7

The east velocity outputs of federated filter

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