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Updated: Oct 25, 2025

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
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Energy-Efficient Time Synchronization Based on Nonlinear Clock Skew Tracking for Underwater Acoustic Networks.

Di Liu1,2,3, Min Zhu1,3,4, Dong Li1,2,3

  • 1Ocean Acoustic Technology Center, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China.

Sensors (Basel, Switzerland)
|August 10, 2021
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Summary

Accurate time synchronization in underwater acoustic networks is achieved using a novel nonlinear clock skew tracking method. This energy-efficient approach improves accuracy and reduces errors compared to existing protocols.

Keywords:
nonlinear clock skewtime synchronizationunderwater acoustic networks

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Area of Science:

  • Underwater Acoustic Networks (UANs)
  • Sensor Networks
  • Signal Processing

Background:

  • Time synchronization (TS) is critical for scheduling and positioning in UANs.
  • Existing TS algorithms struggle with energy efficiency, clock skew estimation, and impulsive noise.
  • Challenges include dynamic clock skew and non-Gaussian noise in underwater environments.

Purpose of the Study:

  • To propose an energy-efficient TS method for UANs.
  • To accurately track time-varying clock skew in dynamic conditions.
  • To suppress impulsive noise and improve synchronization accuracy.

Main Methods:

  • Developed a nonlinear clock skew tracking (NCST) method.
  • Utilized a receiver-only (RO) paradigm for energy efficiency.
  • Employed Gaussian Mixture Model (GMM) for non-Gaussian noise and Particle Filter (PF) for state tracking.

Main Results:

  • NCST-TS significantly reduces accumulative Root Mean Square Errors (RMSE) from 10^-4 s to 10^-5 s.
  • The proposed method demonstrates superior energy efficiency compared to other TS algorithms.
  • Effective suppression of impulsive noise and accurate tracking of clock skew dynamics were achieved.

Conclusions:

  • The NCST-TS method offers a robust and energy-efficient solution for time synchronization in UANs.
  • It effectively addresses challenges posed by nonlinear clock skew and non-Gaussian noise.
  • This advancement is crucial for improving the performance of UANs in various applications.