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This study introduces a 3D motion tracking method using an extended Kalman filter (EKF) and time-delay measurements. The technique accurately estimates source position with minimal depth error, validated by simulations and experiments.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Geophysics

Background:

  • Characterizing non-radial source motion requires sophisticated modeling.
  • Traditional methods may lack the precision for accurate 3D positioning.
  • Time-delay measurements offer a viable input for motion estimation.

Purpose of the Study:

  • To develop and validate a three-dimensional (3D) model for accurate source motion characterization.
  • To employ the extended Kalman filter (EKF) for estimating source position using time-delay data.
  • To assess the method's accuracy through simulations and experimental validation.

Main Methods:

  • Utilized a three-dimensional (3D) model incorporating an extended Kalman filter (EKF) state matrix.
  • Employed time-delay measurements between direct and surface-reflected arrivals as EKF input.
  • Analyzed partial derivatives of distance components and applied iterative filtering for position estimation.

Main Results:

  • Achieved reliable estimation of the source's position in 3D space.
  • Experimental validation demonstrated high accuracy, with depth estimation errors within 1.5%.
  • The extended Kalman filter effectively processed time-delay data for motion tracking.

Conclusions:

  • The proposed extended Kalman filter-based 3D model accurately characterizes non-radial source motion.
  • The method provides precise source localization with minimal error, confirmed by experimental results.
  • This approach offers a robust solution for real-time 3D source tracking applications.