Data fusion algorithm for INS/GPS/Odometer integrated navigation system

Cui Pingyuan; Xu Tianlai

doi:10.1109/ICIEA.2007.4318739

Data fusion algorithm for INS/GPS/Odometer integrated navigation system

Cui Pingyuan^*, Xu Tianlai

^*Corresponding author for this work

Harbin Institute of Technology

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

9 Citations (Scopus)

Abstract

INS/GPS/Odometer are commonly integrated using a federated Kalman filter to provide a robust navigation solution, overcoming their weaknesses. However, the accuracy of federated Kalman filter is degraded in the condition that the statistical characteristics of noise don't be known accurately. The method of federated Kalman filter is improved to perform the INS/GPS/Odometer integrated navigation in this paper. This method uses fuzzy adaptive Kalman filter to detect changes of the measurement noise statistical characteristics and correct them gradually. Meanwhile, weighted coefficient is used to describe the degree of confidence of sub-filters. Simulations in INS/GPS/Odometer integrated navigation system demonstrate that the weighted coefficients of sub-filters with low confidence are decreased adaptively, and the accuracy is improved compared with the federated kalman filter.

Original language	English
Title of host publication	ICIEA 2007
Subtitle of host publication	2007 Second IEEE Conference on Industrial Electronics and Applications
Pages	1893-1897
Number of pages	5
DOIs	https://doi.org/10.1109/ICIEA.2007.4318739
Publication status	Published - 2007
Externally published	Yes
Event	2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007 - Harbin, China Duration: 23 May 2007 → 25 May 2007

Publication series

Name	ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications

Conference

Conference	2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007
Country/Territory	China
City	Harbin
Period	23/05/07 → 25/05/07

Access to Document

10.1109/ICIEA.2007.4318739

Cite this

@inproceedings{e309ccf31b3c4ff4bb2501b940971e88,

title = "Data fusion algorithm for INS/GPS/Odometer integrated navigation system",

abstract = "INS/GPS/Odometer are commonly integrated using a federated Kalman filter to provide a robust navigation solution, overcoming their weaknesses. However, the accuracy of federated Kalman filter is degraded in the condition that the statistical characteristics of noise don't be known accurately. The method of federated Kalman filter is improved to perform the INS/GPS/Odometer integrated navigation in this paper. This method uses fuzzy adaptive Kalman filter to detect changes of the measurement noise statistical characteristics and correct them gradually. Meanwhile, weighted coefficient is used to describe the degree of confidence of sub-filters. Simulations in INS/GPS/Odometer integrated navigation system demonstrate that the weighted coefficients of sub-filters with low confidence are decreased adaptively, and the accuracy is improved compared with the federated kalman filter.",

author = "Cui Pingyuan and Xu Tianlai",

year = "2007",

doi = "10.1109/ICIEA.2007.4318739",

language = "English",

isbn = "1424407370",

series = "ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications",

pages = "1893--1897",

booktitle = "ICIEA 2007",

note = "2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007 ; Conference date: 23-05-2007 Through 25-05-2007",

}

Pingyuan, C & Tianlai, X 2007, Data fusion algorithm for INS/GPS/Odometer integrated navigation system. in ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications., 4318739, ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications, pp. 1893-1897, 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007, Harbin, China, 23/05/07. https://doi.org/10.1109/ICIEA.2007.4318739

Data fusion algorithm for INS/GPS/Odometer integrated navigation system. / Pingyuan, Cui; Tianlai, Xu.
ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications. 2007. p. 1893-1897 4318739 (ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications).

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

TY - GEN

T1 - Data fusion algorithm for INS/GPS/Odometer integrated navigation system

AU - Pingyuan, Cui

AU - Tianlai, Xu

PY - 2007

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N2 - INS/GPS/Odometer are commonly integrated using a federated Kalman filter to provide a robust navigation solution, overcoming their weaknesses. However, the accuracy of federated Kalman filter is degraded in the condition that the statistical characteristics of noise don't be known accurately. The method of federated Kalman filter is improved to perform the INS/GPS/Odometer integrated navigation in this paper. This method uses fuzzy adaptive Kalman filter to detect changes of the measurement noise statistical characteristics and correct them gradually. Meanwhile, weighted coefficient is used to describe the degree of confidence of sub-filters. Simulations in INS/GPS/Odometer integrated navigation system demonstrate that the weighted coefficients of sub-filters with low confidence are decreased adaptively, and the accuracy is improved compared with the federated kalman filter.

AB - INS/GPS/Odometer are commonly integrated using a federated Kalman filter to provide a robust navigation solution, overcoming their weaknesses. However, the accuracy of federated Kalman filter is degraded in the condition that the statistical characteristics of noise don't be known accurately. The method of federated Kalman filter is improved to perform the INS/GPS/Odometer integrated navigation in this paper. This method uses fuzzy adaptive Kalman filter to detect changes of the measurement noise statistical characteristics and correct them gradually. Meanwhile, weighted coefficient is used to describe the degree of confidence of sub-filters. Simulations in INS/GPS/Odometer integrated navigation system demonstrate that the weighted coefficients of sub-filters with low confidence are decreased adaptively, and the accuracy is improved compared with the federated kalman filter.

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SN - 9781424407378

T3 - ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications

SP - 1893

EP - 1897

BT - ICIEA 2007

T2 - 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007

Y2 - 23 May 2007 through 25 May 2007

ER -

Data fusion algorithm for INS/GPS/Odometer integrated navigation system

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