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Underwater terrain-aided navigation system based on combination matching algorithm.

Peijuan Li1, Guoliang Sheng1, Xiaofei Zhang2

  • 1Industrial Center, Nanjing Institute of Technology, Nanjing, 211167, China.

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|March 18, 2018
PubMed
Summary

This study enhances terrain-aided navigation (TAN) for autonomous underwater vehicles (AUVs) by integrating a Kalman filter with the iterated closest contour point (ICCP) algorithm. This improves navigation accuracy and stability, preventing system divergence for long-term underwater missions.

Keywords:
Autonomous underwater vehicleIterated closest contour pointKalman filterTerrain-aided navigation system

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Area of Science:

  • Robotics and Control Systems
  • Navigation and Positioning Technologies
  • Marine Engineering

Background:

  • Strapdown inertial navigation systems (SINS) integrated with terrain-aided navigation (TAN) using the iterated closest contour point (ICCP) algorithm are prone to divergence with large indicative track errors.
  • Autonomous underwater vehicles (AUVs) require high-precision, stable, and reliable navigation for long-term underwater operations.

Purpose of the Study:

  • To develop an improved navigation system for AUVs that mitigates the divergence issues of traditional ICCP-based TAN.
  • To enhance the accuracy and stability of AUV navigation through a novel integrated approach.

Main Methods:

  • The study integrates a Kalman filter into the traditional ICCP algorithm to correct strapdown inertial navigation system (SINS) cumulative errors.
  • A mathematical model for the AUV integrated navigation system and the TAN observation model were established.
  • Simulation experiments were conducted to validate the performance of the proposed algorithm, optimizing the matching point number for precision and time.

Main Results:

  • The proposed combined algorithm demonstrates improved navigation accuracy and stability compared to the traditional ICCP algorithm.
  • The integrated navigation system effectively prevents the divergence of the indicative track.
  • Optimal matching point numbers were identified, enhancing both matching time and precision.

Conclusions:

  • The integrated navigation system meets the stringent requirements for underwater, long-term, and high-precision navigation of AUVs.
  • The Kalman filter integration significantly enhances the robustness and reliability of TAN systems for AUV applications.