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Joint autonomous underwater vehicle and underwater sensor net-works target tracking for underwater applications
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Zhaohong LV, Zhenkai ZHANG, Boonchong SEET, Yi YANG. Joint autonomous underwater vehicle and underwater sensor net-works target tracking for underwater applications[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .
@article{title="Joint autonomous underwater vehicle and underwater sensor net-works target tracking for underwater applications",
author="Zhaohong LV, Zhenkai ZHANG, Boonchong SEET, Yi YANG",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2400869"
}
%0 Journal Article
%T Joint autonomous underwater vehicle and underwater sensor net-works target tracking for underwater applications
%A Zhaohong LV
%A Zhenkai ZHANG
%A Boonchong SEET
%A Yi YANG
%J Journal of Zhejiang University SCIENCE C
%V -1
%N -1
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%@ 2095-9184
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2400869
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T1 - Joint autonomous underwater vehicle and underwater sensor net-works target tracking for underwater applications
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A1 - Yi YANG
J0 - Journal of Zhejiang University Science C
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2400869
Abstract: Because underwater sensor networks (USNs) have limited energy resources due to environmental constraints, it is essential to improve energy utilization. For this purpose, an autonomous underwater vehicle (AUV) with greater onboard com-putation power is utilized to process measurement data, and the mobility of the AUV is leveraged to optimize the USN topology, enhancing tracking accuracy. First, to address the transmission delay of underwater acoustic signals, a centralized extended Kalman filter incorporating a time delay estimation (TD-CEKF) algorithm is proposed. Next, the mathematical relationship between AUV position and USN topology is established, based upon which the optimization target is constructed. Subsequently, the penalty function is introduced to remove the constraints from the objective function, and the optimal AUV position is searched using the gradient descent method to optimize the USN topology. The simulation results demonstrate that the proposed algorithm can effectively overcome the influence of transmission delay on tracking and achieve improved tracking performance.
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