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Distributed Target Tracking With Fading Channels Over Underwater Acoustic Sensor Networks

  • Miaoyi Tang
  • , Meiqin Liu
  • , Senlin Zhang
  • , Ronghao Zheng
  • , Shanling Dong
  • Zhejiang University

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

This article investigates the problem of distributed target tracking via underwater acoustic sensor networks (UASNs) with fading channels. The degradation of signal quality due to wireless channel fading can significantly impact network reliability and subsequently reduce the tracking accuracy. To address this issue, we propose a modified distributed unscented Kalman filter (DUKF) named DUKF-Fc, which takes into account the effects of measurement fluctuation and transmission failure induced by channel fading. The channel estimation error is also considered when designing the estimator and a sufficient condition is established to ensure the stochastic boundedness of the estimation error. The proposed filtering scheme is versatile and possesses wide applicability to numerous scenarios, e.g., tracking a maneuvering underwater target with underwater sensor nodes (USNs) equipped with acoustic sensors. Considering the constraints of network energy resources, the issue of investigating the energy cost of DUKF-Fc is discussed in the simulation and accordingly, the results demonstrate the robustness and energy efficiency of the proposed filtering procedure.

Original languageEnglish
Pages (from-to)13980-13994
Number of pages15
JournalIEEE Internet of Things Journal
Volume11
Issue number8
DOIs
StatePublished - 15 Apr 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Channel fading
  • distributed state estimation (DSE)
  • stochastic stability
  • underwater acoustic sensor networks (UASNs)
  • unscented Kalman filtering

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