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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Project supported by the National Natural Science Foundation of China (Nos. 61531015, 61673345, and 61374021) and the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (Nos. U1609204 and U1709203)
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Zhang, D., Liu, Mq., Zhang, Sl. et al. Mutual-information based weighted fusion for target tracking in underwater wireless sensor networks. Frontiers Inf Technol Electronic Eng 19, 544–556 (2018). https://doi.org/10.1631/FITEE.1601695
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DOI: https://doi.org/10.1631/FITEE.1601695