Dynamic Path Planning for Autonomous Underwater Vehicle Assisted Localization of Underwater Acoustic Aensor Networks

HUANG Peishuo; WANG Yiyin; GUAN Xinping; HUANG Mengxing

doi:10.11999/JEIT211432

Volume 44 Issue 6

Jun. 2022

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(6): 1927-1936

HUANG Peishuo, WANG Yiyin, GUAN Xinping, HUANG Mengxing. Dynamic Path Planning for Autonomous Underwater Vehicle Assisted Localization of Underwater Acoustic Aensor Networks[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1927-1936. doi: 10.11999/JEIT211432

Citation:

HUANG Peishuo, WANG Yiyin, GUAN Xinping, HUANG Mengxing. Dynamic Path Planning for Autonomous Underwater Vehicle Assisted Localization of Underwater Acoustic Aensor Networks[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1927-1936. doi: 10.11999/JEIT211432

Citation:

HUANG Peishuo, WANG Yiyin, GUAN Xinping, HUANG Mengxing. Dynamic Path Planning for Autonomous Underwater Vehicle Assisted Localization of Underwater Acoustic Aensor Networks[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1927-1936. doi: 10.11999/JEIT211432

PDF( 9297 KB)

Dynamic Path Planning for Autonomous Underwater Vehicle Assisted Localization of Underwater Acoustic Aensor Networks

doi: 10.11999/JEIT211432

HUANG Peishuo^{1, 3},
WANG Yiyin^{2, 3
,
,},
GUAN Xinping^{2, 3},
HUANG Mengxing¹

1.
School of Information and Communication Engineering, Hainan University, Haikou 570228, China
2.
Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
3.
Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China

Funds: The National Natural Science Foundation of China (61773264, 61633017), The Oceanic Interdisciplinary Program of Shanghai Jiao Tong University (SL2020MS011, SL2020MS015)

Received Date: 2021-12-06
Rev Recd Date: 2022-05-24

Available Online: 2022-05-26

Publish Date: 2022-06-21

Abstract

Abstract

Due to various effects, such as ocean currents, locations of sensor nodes have to be updated in Underwater Acoustic Sensors Networks (UASNs). In UASNs localization, using an Autonomous Underwater Vehicle (AUV) as the mobile anchor can reduce the localization cost. However, the energy utilization of AUV is not efficient. In order to improve the energy utilization of AUV, a dynamic path planning method is proposed for an AUV-aided localization for UASNs. In this method, the location correction process is regarded as a process of reducing the entropy of location information of sensor nodes. In dynamic path planning, the next target location of the AUV is planned according to the sensor node location information and the expected AUV energy consumption. The greedy algorithm is used to select the location that can obtain the maximum ratio of the expectation of the information gain and mobile energy consumption as the target location. The simulation show that the proposed algorithm can improve the energy efficiency while ensuring the positioning accuracy.

FullText(HTML)

References(20)

References

[1]	HAN Guangjie, JIANG Jinfang, ZHANG Chenyu, et al. A survey on mobile anchor node assisted localization in wireless sensor networks[J]. IEEE Communications Surveys & Tutorials, 2016, 18(3): 2220–2243. doi: 10.1109/COMST.2016.2544751
[2]	KOUTSONIKOLAS D, DAS S M, and HU Y C. Path planning of mobile landmarks for localization in wireless sensor networks[J]. Computer Communications, 2007, 30(13): 2577–2592. doi: 10.1016/j.comcom.2007.05.048
[3]	HAN Guangjie, YANG Xuan, LIU Li, et al. A disaster management-oriented path planning for mobile anchor node-based localization in wireless sensor networks[J]. IEEE Transactions on Emerging Topics in Computing, 2020, 8(1): 115–125. doi: 10.1109/TETC.2017.2687319
[4]	赵方, 马严, 罗海勇, 等. 一种基于网络密度分簇的移动信标辅助定位方法[J]. 电子与信息学报, 2009, 31(12): 2988–2992. doi: 10.3724/SP.J.1146.2008.01532 ZHAO Fang, MA Yan, LUO Haiyong, et al. A mobile beacon-assisted node localization algorithm using network-density-based clustering for wireless sensor networks[J]. Journal of Electronics &Information Technology, 2009, 31(12): 2988–2992. doi: 10.3724/SP.J.1146.2008.01532
[5]	SALLOUHA H, AZARI M M, and POLLIN S. Energy-constrained UAV trajectory design for ground node localization[C]. 2018 IEEE Global Communications Conference, Abu Dhabi, United Arab Emirates, 2018: 1–7.
[6]	ALOMARI A, PHILLIPS W, ASLAM N, et al. Dynamic fuzzy-logic based path planning for mobility-assisted localization in wireless sensor networks[J]. Sensors, 2017, 17(8): 1904. doi: 10.3390/s17081904
[7]	EROL M, VIEIRA L F M, and GERLA M. AUV-aided localization for underwater sensor networks[C]. International Conference on Wireless Algorithms, Systems and Applications, Chicago, USA, 2007: 44–54.
[8]	XIA Youjie, WANG Yiyin, MA Xiaoli, et al. Joint time synchronization and localization for underwater acoustic sensor networks[C]. The 10th International Conference on Underwater Networks & Systems, Arlington, USA, 2015: 43.
[9]	MRIDULA K M and AMEER P M. Localization under anchor node uncertainty for underwater acoustic sensor networks[J]. International Journal of Communication Systems, 2018, 31(2): e3445. doi: 10.1002/dac.3445
[10]	ZHANG Wenbo, HAN Guangjie, WANG Xin, et al. A node location algorithm based on node movement prediction in underwater acoustic sensor networks[J]. IEEE Transactions on Vehicular Technology, 2020, 69(3): 3166–3178. doi: 10.1109/TVT.2019.2963406
[11]	SU Yishan, GUO Lei, JIN Zhigang, et al. A mobile-beacon-based iterative localization mechanism in large-scale underwater acoustic sensor networks[J]. IEEE Internet of Things Journal, 2021, 8(5): 3653–3664. doi: 10.1109/JIOT.2020.3023556
[12]	XU Tingting, WANG Jingjing, SHI Wei, et al. A localization algorithm using a mobile anchor node based on region determination in underwater wireless sensor networks[J]. Journal of Ocean University of China, 2019, 18(2): 394–402. doi: 10.1007/s11802-019-3724-x
[13]	HAN Guangjie, XU Huihui, JIANG Jinfang, et al. Path planning using a mobile anchor node based on trilateration in wireless sensor networks[J]. Wireless Communications and Mobile Computing, 2013, 13(14): 1324–1336. doi: 10.1002/wcm.1192
[14]	SU Ruoyu, ZHANG Dengyin, LI Cheng, et al. Localization and data collection in AUV-aided underwater sensor networks: Challenges and opportunities[J]. IEEE Network, 2019, 33(6): 86–93. doi: 10.1109/MNET.2019.1800425
[15]	HAN Shuai, XU Sai, MENG Weixiao, et al. Dense-device-enabled cooperative networks for efficient and secure transmission[J]. IEEE Network, 2018, 32(2): 100–106. doi: 10.1109/MNET.2018.1700292
[16]	ZHUO Xiaoxiao, LIU Meiyan, WEI Yan, et al. AUV-aided energy-efficient data collection in underwater acoustic sensor networks[J]. IEEE Internet of Things Journal, 2020, 7(10): 10010–10022. doi: 10.1109/JIOT.2020.2988697
[17]	KHAN F A, KHAN S A, TURGUT D, et al. Greedy path planning for maximizing value of information in underwater sensor networks[C]. The 39th Annual IEEE Conference on Local Computer Networks Workshops, Edmonton, Canada, 2014: 610–615.
[18]	GJANCI P, PETRIOLI C, BASAGNI S, et al. Path finding for maximum value of information in multi-modal underwater wireless sensor networks[J]. IEEE Transactions on Mobile Computing, 2018, 17(2): 404–418. doi: 10.1109/TMC.2017.2706689
[19]	CHEN Shihan, CHEN Yougan, ZHU Jianying, et al. Path-planning analysis of AUV-aided mobile data collection in UWA cooperative sensor networks[C]. 2020 IEEE International Conference on Signal Processing, Communications and Computing, Macau, China, 2020: 1–5.
[20]	SHANNON C E. A mathematical theory of communication[J]. The Bell System Technical Journal, 1948, 27(3): 379–423. doi: 10.1002/j.1538-7305.1948.tb01338.x