Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement

Kun Yang; Chunlan Jiang; Ming Li

doi:10.1109/ICUS48101.2019.8995998

Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement

Kun Yang, Chunlan Jiang, Ming Li

School of Mechatronical Engineering

Beijing Institute of Technology

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

Abstract

Target tracking is one of the key technologies in the military application of wireless sensor networks. This paper aims at the characteristics of wireless sensor network nodes, which have limited computing capacity but can conduct data fusion through wireless communication, to improve tracking accuracy from two aspects. On the one hand, an adaptive bias-compensated pseudo-measurement Kalman filter based on process noise is proposed, on the other hand, an adaptive weighted fusion algorithm based on innovation is proposed. Through multiple simulations, the proposed algorithms can significantly improve the tracking accuracy and robustness of the system on the premise of low computational complexity.

Original language	English
Title of host publication	Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	261-266
Number of pages	6
ISBN (Electronic)	9781728137926
DOIs	https://doi.org/10.1109/ICUS48101.2019.8995998
Publication status	Published - Oct 2019
Event	2019 IEEE International Conference on Unmanned Systems, ICUS 2019 - Beijing, China Duration: 17 Oct 2019 → 19 Oct 2019

Publication series

Name	Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

Conference

Conference	2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Country/Territory	China
City	Beijing
Period	17/10/19 → 19/10/19

Keywords

innovation
process noise
pseudo-measurement Kalman filter
track fusion

Access to Document

10.1109/ICUS48101.2019.8995998

Cite this

Yang, K., Jiang, C., & Li, M. (2019). Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement. In Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019 (pp. 261-266). Article 8995998 (Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICUS48101.2019.8995998

@inproceedings{f4ddc1ebce6343ef88011535e26fbccc,

title = "Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement",

abstract = "Target tracking is one of the key technologies in the military application of wireless sensor networks. This paper aims at the characteristics of wireless sensor network nodes, which have limited computing capacity but can conduct data fusion through wireless communication, to improve tracking accuracy from two aspects. On the one hand, an adaptive bias-compensated pseudo-measurement Kalman filter based on process noise is proposed, on the other hand, an adaptive weighted fusion algorithm based on innovation is proposed. Through multiple simulations, the proposed algorithms can significantly improve the tracking accuracy and robustness of the system on the premise of low computational complexity.",

keywords = "innovation, process noise, pseudo-measurement Kalman filter, track fusion",

author = "Kun Yang and Chunlan Jiang and Ming Li",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Unmanned Systems, ICUS 2019 ; Conference date: 17-10-2019 Through 19-10-2019",

year = "2019",

month = oct,

doi = "10.1109/ICUS48101.2019.8995998",

language = "English",

series = "Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019",

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

pages = "261--266",

booktitle = "Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019",

address = "United States",

}

Yang, K, Jiang, C & Li, M 2019, Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement. in Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019., 8995998, Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019, Institute of Electrical and Electronics Engineers Inc., pp. 261-266, 2019 IEEE International Conference on Unmanned Systems, ICUS 2019, Beijing, China, 17/10/19. https://doi.org/10.1109/ICUS48101.2019.8995998

Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement. / Yang, Kun; Jiang, Chunlan ; Li, Ming.
Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 261-266 8995998 (Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019).

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

TY - GEN

T1 - Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement

AU - Yang, Kun

AU - Jiang, Chunlan

AU - Li, Ming

PY - 2019/10

Y1 - 2019/10

N2 - Target tracking is one of the key technologies in the military application of wireless sensor networks. This paper aims at the characteristics of wireless sensor network nodes, which have limited computing capacity but can conduct data fusion through wireless communication, to improve tracking accuracy from two aspects. On the one hand, an adaptive bias-compensated pseudo-measurement Kalman filter based on process noise is proposed, on the other hand, an adaptive weighted fusion algorithm based on innovation is proposed. Through multiple simulations, the proposed algorithms can significantly improve the tracking accuracy and robustness of the system on the premise of low computational complexity.

AB - Target tracking is one of the key technologies in the military application of wireless sensor networks. This paper aims at the characteristics of wireless sensor network nodes, which have limited computing capacity but can conduct data fusion through wireless communication, to improve tracking accuracy from two aspects. On the one hand, an adaptive bias-compensated pseudo-measurement Kalman filter based on process noise is proposed, on the other hand, an adaptive weighted fusion algorithm based on innovation is proposed. Through multiple simulations, the proposed algorithms can significantly improve the tracking accuracy and robustness of the system on the premise of low computational complexity.

KW - innovation

KW - process noise

KW - pseudo-measurement Kalman filter

KW - track fusion

UR - https://www.scopus.com/pages/publications/85080887236

U2 - 10.1109/ICUS48101.2019.8995998

DO - 10.1109/ICUS48101.2019.8995998

M3 - Conference contribution

AN - SCOPUS:85080887236

T3 - Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

SP - 261

EP - 266

BT - Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

Y2 - 17 October 2019 through 19 October 2019

ER -

Yang K, Jiang C , Li M. Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement. In Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 261-266. 8995998. (Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019). doi: 10.1109/ICUS48101.2019.8995998

Research on Adaptive Fusion Tracking Algorithm for Bearings-Only Measurement

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