Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms

Rui Song; Teng Long; Zhu Wang; Yan Cao; Guangtong Xu

doi:10.1109/GNCC42960.2018.9019171

Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms

Rui Song, Teng Long, Zhu Wang, Yan Cao, Guangtong Xu

School of Aerospace Engineering

Beijing Institute of Technology

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

9 Citations (Scopus)

Abstract

To solve the problem of cooperative target tracking considering ground moving-targets and threats, a novel approach for multiple unmanned aerial vehicles (multi-UAV) cooperative target tracking using sparse A^{∗} search and Standoff tracking algorithms is proposed. Firstly, sparse A^{∗} search algorithm is introduced to generate multiple paths for UAVs subject to the threats and UAV kinematics constraints. And multi-UAV rendezvous at a predefined formation nearby the moving-target. Then, considering the target tracking distance and relative phase angle constraints, the Standoff tracking algorithm is utilized to generate cooperative tracking paths. Simulation results demonstrate that the multi-UAV cooperative target tracking method can effectively avoid threats and achieve persistent moving-target tracking and monitoring in the mission areas.

Original language	English
Title of host publication	2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538611715
DOIs	https://doi.org/10.1109/GNCC42960.2018.9019171
Publication status	Published - Aug 2018
Event	2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018 - Xiamen, China Duration: 10 Aug 2018 → 12 Aug 2018

Publication series

Name	2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018

Conference

Conference	2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
Country/Territory	China
City	Xiamen
Period	10/08/18 → 12/08/18

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10.1109/GNCC42960.2018.9019171

Cite this

Song, R., Long, T., Wang, Z., Cao, Y., & Xu, G. (2018). Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms. In 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018 Article 9019171 (2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GNCC42960.2018.9019171

@inproceedings{97ad4cd0ff084294bc31fc860c9e4a64,

title = "Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms",

abstract = "To solve the problem of cooperative target tracking considering ground moving-targets and threats, a novel approach for multiple unmanned aerial vehicles (multi-UAV) cooperative target tracking using sparse A^{∗} search and Standoff tracking algorithms is proposed. Firstly, sparse A^{∗} search algorithm is introduced to generate multiple paths for UAVs subject to the threats and UAV kinematics constraints. And multi-UAV rendezvous at a predefined formation nearby the moving-target. Then, considering the target tracking distance and relative phase angle constraints, the Standoff tracking algorithm is utilized to generate cooperative tracking paths. Simulation results demonstrate that the multi-UAV cooperative target tracking method can effectively avoid threats and achieve persistent moving-target tracking and monitoring in the mission areas.",

author = "Rui Song and Teng Long and Zhu Wang and Yan Cao and Guangtong Xu",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018 ; Conference date: 10-08-2018 Through 12-08-2018",

year = "2018",

month = aug,

doi = "10.1109/GNCC42960.2018.9019171",

language = "English",

series = "2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018",

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

booktitle = "2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018",

address = "United States",

}

Song, R, Long, T, Wang, Z, Cao, Y & Xu, G 2018, Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms. in 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018., 9019171, 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018, Xiamen, China, 10/08/18. https://doi.org/10.1109/GNCC42960.2018.9019171

Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms. / Song, Rui; Long, Teng; Wang, Zhu et al.
2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 9019171 (2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018).

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

TY - GEN

T1 - Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms

AU - Song, Rui

AU - Long, Teng

AU - Wang, Zhu

AU - Cao, Yan

AU - Xu, Guangtong

PY - 2018/8

Y1 - 2018/8

N2 - To solve the problem of cooperative target tracking considering ground moving-targets and threats, a novel approach for multiple unmanned aerial vehicles (multi-UAV) cooperative target tracking using sparse A^{∗} search and Standoff tracking algorithms is proposed. Firstly, sparse A^{∗} search algorithm is introduced to generate multiple paths for UAVs subject to the threats and UAV kinematics constraints. And multi-UAV rendezvous at a predefined formation nearby the moving-target. Then, considering the target tracking distance and relative phase angle constraints, the Standoff tracking algorithm is utilized to generate cooperative tracking paths. Simulation results demonstrate that the multi-UAV cooperative target tracking method can effectively avoid threats and achieve persistent moving-target tracking and monitoring in the mission areas.

AB - To solve the problem of cooperative target tracking considering ground moving-targets and threats, a novel approach for multiple unmanned aerial vehicles (multi-UAV) cooperative target tracking using sparse A^{∗} search and Standoff tracking algorithms is proposed. Firstly, sparse A^{∗} search algorithm is introduced to generate multiple paths for UAVs subject to the threats and UAV kinematics constraints. And multi-UAV rendezvous at a predefined formation nearby the moving-target. Then, considering the target tracking distance and relative phase angle constraints, the Standoff tracking algorithm is utilized to generate cooperative tracking paths. Simulation results demonstrate that the multi-UAV cooperative target tracking method can effectively avoid threats and achieve persistent moving-target tracking and monitoring in the mission areas.

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DO - 10.1109/GNCC42960.2018.9019171

M3 - Conference contribution

AN - SCOPUS:85082480580

T3 - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018

BT - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018

Y2 - 10 August 2018 through 12 August 2018

ER -

Song R, Long T, Wang Z, Cao Y, Xu G. Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms. In 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 9019171. (2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018). doi: 10.1109/GNCC42960.2018.9019171

Multi-UAV Cooperative Target Tracking Method using sparse A search and Standoff tracking algorithms

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