A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal

He Kanghui; Dong Chaoyang

doi:10.1109/ICPICS47731.2019.8942402

A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal

He Kanghui
, Dong Chaoyang

航空科学与工程学院

Beihang University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

3 引用（Scopus）

摘要

For the UAV inertial/GPS integrated navigation system, considering the problem of GPS data interruption in navigation process, this technical paper designs an improved sensors fusion algorithm. Combining the traditional extended Kalman filter (EKF) technology with strong tracking filter, a fuzzy strong tracking extended Kalman filter algorithm is designed by using the membership function of the fuzzy theory. Then the navigation simulation model of UAV is established. The simulation results show that the improved algorithm can quickly adapt to the sudden change of GPS signal, that is, when the GPS signal restores from the fault state to the normal state, the improved algorithm can converge to the stable state more quickly than the EKF algorithm, and complete the estimation of flight state again. At the same time, compared with EKF and strong tracking extended Kalman filter (SKEKF), the improved algorithm in this paper has higher estimation accuracy.

源语言	英语
主期刊名	2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019
出版商	Institute of Electrical and Electronics Engineers Inc.
页	254-259
页数	6
ISBN（电子版）	9781728137209
DOI	https://doi.org/10.1109/ICPICS47731.2019.8942402
出版状态	已出版 - 7月 2019
活动	2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019 - Shenyang, 中国期限: 12 7月 2019 → 14 7月 2019

出版系列

姓名	2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019

会议

会议	2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019
国家/地区	中国
市	Shenyang
时期	12/07/19 → 14/07/19

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 7 经济适用的清洁能源

访问文件

10.1109/ICPICS47731.2019.8942402

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链接到 Scopus 的出版物

引用此

Kanghui, H., & Chaoyang, D. (2019). A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal. 在 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019 (页码 254-259). 文章 8942402 (2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPICS47731.2019.8942402

Kanghui, He ; Chaoyang, Dong. / A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal. 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 页码 254-259 (2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019).

@inproceedings{85ed079293534bcda3ce4ef960fc107f,

title = "A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal",

abstract = "For the UAV inertial/GPS integrated navigation system, considering the problem of GPS data interruption in navigation process, this technical paper designs an improved sensors fusion algorithm. Combining the traditional extended Kalman filter (EKF) technology with strong tracking filter, a fuzzy strong tracking extended Kalman filter algorithm is designed by using the membership function of the fuzzy theory. Then the navigation simulation model of UAV is established. The simulation results show that the improved algorithm can quickly adapt to the sudden change of GPS signal, that is, when the GPS signal restores from the fault state to the normal state, the improved algorithm can converge to the stable state more quickly than the EKF algorithm, and complete the estimation of flight state again. At the same time, compared with EKF and strong tracking extended Kalman filter (SKEKF), the improved algorithm in this paper has higher estimation accuracy.",

keywords = "extended kalman filter, integrated navigation, membership function, strong trracking",

author = "He Kanghui and Dong Chaoyang",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019 ; Conference date: 12-07-2019 Through 14-07-2019",

year = "2019",

month = jul,

doi = "10.1109/ICPICS47731.2019.8942402",

language = "英语",

series = "2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "254--259",

booktitle = "2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019",

address = "美国",

}

Kanghui, H & Chaoyang, D 2019, A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal. 在 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019., 8942402, 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019, Institute of Electrical and Electronics Engineers Inc., 页码 254-259, 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019, Shenyang, 中国, 12/07/19. https://doi.org/10.1109/ICPICS47731.2019.8942402

A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal. / Kanghui, He; Chaoyang, Dong.
2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 页码 254-259 8942402 (2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal

AU - Kanghui, He

AU - Chaoyang, Dong

PY - 2019/7

Y1 - 2019/7

N2 - For the UAV inertial/GPS integrated navigation system, considering the problem of GPS data interruption in navigation process, this technical paper designs an improved sensors fusion algorithm. Combining the traditional extended Kalman filter (EKF) technology with strong tracking filter, a fuzzy strong tracking extended Kalman filter algorithm is designed by using the membership function of the fuzzy theory. Then the navigation simulation model of UAV is established. The simulation results show that the improved algorithm can quickly adapt to the sudden change of GPS signal, that is, when the GPS signal restores from the fault state to the normal state, the improved algorithm can converge to the stable state more quickly than the EKF algorithm, and complete the estimation of flight state again. At the same time, compared with EKF and strong tracking extended Kalman filter (SKEKF), the improved algorithm in this paper has higher estimation accuracy.

AB - For the UAV inertial/GPS integrated navigation system, considering the problem of GPS data interruption in navigation process, this technical paper designs an improved sensors fusion algorithm. Combining the traditional extended Kalman filter (EKF) technology with strong tracking filter, a fuzzy strong tracking extended Kalman filter algorithm is designed by using the membership function of the fuzzy theory. Then the navigation simulation model of UAV is established. The simulation results show that the improved algorithm can quickly adapt to the sudden change of GPS signal, that is, when the GPS signal restores from the fault state to the normal state, the improved algorithm can converge to the stable state more quickly than the EKF algorithm, and complete the estimation of flight state again. At the same time, compared with EKF and strong tracking extended Kalman filter (SKEKF), the improved algorithm in this paper has higher estimation accuracy.

KW - extended kalman filter

KW - integrated navigation

KW - membership function

KW - strong trracking

UR - https://www.scopus.com/pages/publications/85077968866

U2 - 10.1109/ICPICS47731.2019.8942402

DO - 10.1109/ICPICS47731.2019.8942402

M3 - 会议稿件

AN - SCOPUS:85077968866

T3 - 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019

SP - 254

EP - 259

BT - 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019

Y2 - 12 July 2019 through 14 July 2019

ER -

Kanghui H, Chaoyang D. A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal. 在 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 页码 254-259. 8942402. (2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019). doi: 10.1109/ICPICS47731.2019.8942402

A Fuzzy Strong Tracking Extended Kalman Filter for UAV Navigation Considering Interruption of GPS Signal

摘要

出版系列

会议

联合国可持续发展目标

访问文件

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学术指纹

引用此