基于互信息的水下无线传感器网络目标跟踪与加权融合

张铎; 刘妹琴; 张森林; 樊臻; 张群飞

doi:10.1631/FITEE.1601695

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基于互信息的水下无线传感器网络目标跟踪与加权融合

常规文章 | Updated：2022-05-19

- 基于互信息的水下无线传感器网络目标跟踪与加权融合
- Mutual-information based weighted fusion for target tracking in underwater wireless sensor networks
- 信息与电子工程前沿（英文） 2018年19卷第4期页码：544-556
- Affiliations：
  
  State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
  College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
  School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China
- Author bio：
  
  [ "Duo ZHANG, E-mail:zhangduo@zju.edu.cn" ]
  Mei-qin LIU, E-mail:liumeiqin@zju.edu.cn
  [ "Sen-lin ZHANG, E-mail:slzhang@zju.edu.cn" ]
  [ "Zhen FAN, E-mail:fanzhen@zju.edu.cn" ]
  [ "Qun-fei ZHANG, E-mail:zhangqf@nwpu.edu.cn" ]
- Funds：
  
  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)
- DOI：10.1631/FITEE.1601695
  中图分类号： TN92
- 收稿：2016-11-09，
  
  修回：2018-;4-;3，
  
  纸质出版：2018-04
- Accepted：
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张铎, 刘妹琴, 张森林, 等. 基于互信息的水下无线传感器网络目标跟踪与加权融合[J]. 信息与电子工程前沿（英文）, 2018,19(4):544-556.

Duo ZHANG, Mei-qin LIU, Sen-lin ZHANG, et al. 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.
张铎, 刘妹琴, 张森林, 等. 基于互信息的水下无线传感器网络目标跟踪与加权融合[J]. 信息与电子工程前沿（英文）, 2018,19(4):544-556. DOI： 10.1631/FITEE.1601695.

Duo ZHANG, Mei-qin LIU, Sen-lin ZHANG, et al. 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. DOI： 10.1631/FITEE.1601695.

摘要

水下无线传感器网络为水下目标跟踪问题提供了可靠有效支持，但水下网络能量和带宽资源有限，只能选择一部分节点参与跟踪任务。融合中心通过收集、融合各个传感器发送的量测进行目标跟踪，因此设计更好的融合权值极为重要。针对水下目标跟踪中的加权融合问题，首先通过计算量测与目标状态之间的互信息，利用互信息衡量融合权重；其次利用互信息融合权重设计一种新的多传感器加权粒子滤波算法，利用克拉美罗（Cramer-Rao）下界设计节点选择方案，以提高跟踪算法效率；最后通过仿真实验对算法进行验证。仿真结果表明，通过选择合适融合权值，目标状态估计精度显著提高。

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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