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Coordinated target tracking in sensor networks by maximizing mutual information

  • Yintao Wang EMAIL logo and Fuchao Xie
Published/Copyright: October 18, 2022

Abstract

This paper addresses the problem of coordinated target tracking in sensor networks. For a typical target tracking scene with nonlinear bearing-only measurements, we first investigate the mutual information between multiple sensors and the target state. To improve the performance of target tracking, we analyzed the relative positions between sensor agents and the target to be tracked and derived the optimal positions for sensors in the network by mutual information maximization. Simulation results are presented and discussed to demonstrate that the performance of estimated target states could be improved by the proposed method.


Corresponding author: Yintao Wang, School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, P.R. China; and National Key Lab of Underwater Information and Control, Xi’an, Shaanxi, P.R.China, E-mail:

Funding source: National Natural Science Foundation of China

Award Identifier / Grant number: U2141238

Award Identifier / Grant number: 61472326

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work was supported by the National Natural Science Foundation of China via Grants U2141238 and 61472326.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Received: 2018-04-13
Revised: 2020-06-16
Accepted: 2022-09-29
Published Online: 2022-10-18
Published in Print: 2022-12-16

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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