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Optimal Sensor Formation for 3D Cooperative Localization of AUVs Using Time Difference of Arrival (TDOA) Method.

Xu Bo1, Asghar A Razzaqi2, Xiaoyu Wang3

  • 1College of Automation, Harbin Engineering University, Harbin 150001, China. xubocarter@hrbeu.edu.cn.

Sensors (Basel, Switzerland)
|December 19, 2018
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Summary

This study presents an optimal sensor formation method for cooperative localization of autonomous underwater vehicles (AUVs) using Time Difference of Arrival (TDOA). The approach ensures efficient computation for enhanced underwater navigation and tracking.

Keywords:
Fisher Information MatrixTime Difference of Arrival (TDOA)autonomous underwater vehicles (AUVs)cooperative localizationoptimal formation

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Area of Science:

  • Robotics
  • Navigation Systems
  • Oceanography

Background:

  • Cooperative localization of autonomous underwater vehicles (AUVs) is crucial for underwater applications.
  • Optimal sensor placement is critical for accurate cooperative localization using Time Difference of Arrival (TDOA) measurements.

Purpose of the Study:

  • To present a novel method for determining the optimal formation of sensor AUVs for three-dimensional (3D) cooperative localization.
  • To enhance the accuracy and efficiency of underwater AUV navigation and tracking.

Main Methods:

  • Derived an evaluation function based on Fisher Information Matrix (FIM) theory for optimal sensor formation.
  • Employed an iterative stepping algorithm to solve the evaluation function, ensuring limited computational complexity.
  • Investigated the impact of reference sensor position and target AUV operating depth on optimal formation.

Main Results:

  • Developed a method to calculate optimal sensor AUV formations for single and multiple target localization.
  • Demonstrated that the proposed algorithm maintains computational efficiency with an increasing number of sensor AUVs.
  • Analyzed the influence of various parameters on the optimal sensor configuration.

Conclusions:

  • The proposed method effectively determines optimal sensor formations for TDOA-based cooperative localization of AUVs.
  • The iterative algorithm provides an efficient solution for complex underwater navigation scenarios.
  • The study provides insights into practical implementation considerations, including target position uncertainty.