A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
Volume 10
Issue 4
IEEE/CAA Journal of Automatica Sinica
| Citation: | L. Y. Zheng, M. Q. Liu, S. L. Zhang, and J. Lan, “A novel sensor scheduling algorithm based on deep reinforcement learning for bearing-only target tracking in UWSNs,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 1077–1079, Apr. 2023. doi: 10.1109/JAS.2023.123159
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J. Luo, H. Ying, and L. Fan, “Underwater acoustic target tracking: A review,” Sensors, vol. 18, no. 1, p. 112, 2018. doi: 10.3390/s18010112
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C. H. Yu, J. C. Lee, J. W. Choi, M.-K. Park, and D. J. Kang, “Energy efficient distributed interacting multiple model filter in UWSNs,” in Proc. 12th Int. Conf. Control, Automation and Syst., 2012, pp. 1093–1098.
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| [3] |
S. Zhang, H. Chen, and M. Liu, “Adaptive sensor scheduling for target tracking in underwater wireless sensor networks,” in Proc. Int. Conf. Mechatronics Control, 2014, pp. 55–60.
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| [4] |
X. Han, M. Liu, S. Zhang, and Q. Zhang, “A multi-node cooperative bearing-only target passive tracking algorithm via UWSNs,” IEEE Sensors J., vol. 19, no. 22, pp. 10609–10623, 2019.
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| [5] |
A. Feriani and E. Hossain, “Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial,” IEEE Commu. Surveys & Tutorials, vol. 23, no. 2, pp. 1226–1252, 2021
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| [6] |
R. Su, Z. Gong, D. Zhang, C. Li, Y. Chen, and R. Venkatesan, “An adaptive asynchronous wake-up scheme for underwater acoustic sensor networks using deep reinforcement learning,” IEEE Trans. Vehicular Technology, vol. 70, no. 2, pp. 1851–1865, 2021.
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X. R. Li and V. P. Jilkov, “Survey of maneuvering target tracking. Part I. Dynamic models,” IEEE Trans. Aerospace and Electronic Syst., vol. 39, no. 4, pp. 1333–1364, 2003.
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X. Leong, A. S. Ramaswamy, A. Quevedo, and D. E. Karl, “Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems,” Automatica, vol. 113, p. 108759, 2020.
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W. Cao, J. Lan, and X. R. Li, “Joint tracking and classification based on recursive joint decision and estimation using multi-sensor data,” in Proc. 17th Intern. Conf. Information Fusion, 2014, pp. 1–8.
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H. Song, Y. Liu, J. Zhao, J. Liu, and G. Wu, “Prioritized replay dueling DDQN based grid-edge control of community energy storage system,” IEEE Trans. Smart Grid, vol. 12, no. 6, pp. 4950–4961, 2021.
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W. Lee and H. Y. Kim, “Genetic algorithm implementation in python,” in Proc. 4th Annual ACIS International Conf. Computer and Infor. Science, 2005, pp. 8–11.
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