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A Fusion Tracking Algorithm for Electro-Optical Theodolite Based on the Three-State Transition Model.

Shixue Zhang1, Houfeng Wang2, Liduo Song1

  • 1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

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This study introduces a new fusion tracking algorithm for electro-optical theodolites, ensuring stable measurements during sensor interference or failure through adaptive weighted fusion and autonomous sensor switching.

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data fusionfusion trackingphotoelectric theodoliterange measurement and control

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Area of Science:

  • Control Systems Engineering
  • Optical Measurement Technology
  • Robotics and Automation

Background:

  • Electro-optical theodolites require stable tracking for accurate measurements.
  • Closed-loop systems face challenges with sensor interference and failure.
  • Existing tracking methods may lack robustness in dynamic environments.

Purpose of the Study:

  • To develop a novel autonomous stable tracking approach for electro-optical theodolites.
  • To enhance the reliability and precision of theodolite measurements under adverse conditions.
  • To introduce a robust fusion tracking algorithm capable of handling sensor anomalies.

Main Methods:

  • Implemented a multi-sensor adaptive weighted fusion algorithm.
  • Developed a fusion tracking algorithm based on a three-state transition model.
  • Utilized a refined recursive formula for error covariance estimation with attenuation factors and least squares extrapolation.

Main Results:

  • The proposed algorithm ensures autonomous and stable measurement of the theodolite.
  • Demonstrated swift autonomous sensor switching during interference or sensor failure.
  • Experimental results confirmed precise and consistent data generation across various scenarios.

Conclusions:

  • The novel approach effectively addresses autonomous stable tracking issues in electro-optical theodolites.
  • The algorithm provides robust performance and reliable data acquisition.
  • This methodology enhances the operational stability and accuracy of tracking systems.