CLC number: TN92
On-line Access: 2018-06-07
Received: 2016-11-09
Revision Accepted: 2017-03-14
Crosschecked: 2018-04-03
Cited: 0
Clicked: 7475
Duo Zhang, Mei-qin Liu, Sen-lin Zhang, Zhen Fan, Qun-fei Zhang. Mutual-information based weighted fusion for target tracking in underwater wireless sensor networks[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(4): 544-556.
@article{title="Mutual-information based weighted fusion for target tracking in underwater wireless sensor networks",
author="Duo Zhang, Mei-qin Liu, Sen-lin Zhang, Zhen Fan, Qun-fei Zhang",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="19",
number="4",
pages="544-556",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601695"
}
%0 Journal Article
%T Mutual-information based weighted fusion for target tracking in underwater wireless sensor networks
%A Duo Zhang
%A Mei-qin Liu
%A Sen-lin Zhang
%A Zhen Fan
%A Qun-fei Zhang
%J Frontiers of Information Technology & Electronic Engineering
%V 19
%N 4
%P 544-556
%@ 2095-9184
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601695
TY - JOUR
T1 - Mutual-information based weighted fusion for target tracking in underwater wireless sensor networks
A1 - Duo Zhang
A1 - Mei-qin Liu
A1 - Sen-lin Zhang
A1 - Zhen Fan
A1 - Qun-fei Zhang
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 19
IS - 4
SP - 544
EP - 556
%@ 2095-9184
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1601695
Abstract: underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to limited energy and bandwidth resources, only a small number of nodes are selected to track a target at each interval. Because all measurements are fused together to provide information in a fusion center, fusion weights of all selected nodes may affect the performance of target tracking. As far as we know, almost all existing tracking schemes neglect this problem. We study a weighted fusion scheme for target tracking in UWSNs. First, because the mutual information (MI) between a node's measurement and the target state can quantify target information provided by the node, it is calculated to determine proper fusion weights. Second, we design a novel multi-sensor weighted particle filter (MSWPF) using fusion weights determined by MI. Third, we present a local node selection scheme based on posterior Cramer-Rao lower bound (PCRLB) to improve tracking efficiency. Finally, simulation results are presented to verify the performance improvement of our scheme with proper fusion weights.
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