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Automatic Identification System (AIS) Dynamic Data Integrity Monitoring and Trajectory Tracking Based on the

Krzysztof Jaskólski1, Łukasz Marchel1, Andrzej Felski1

  • 1Department of Navigation and Maritime Hydrography, Polish Naval Academy, ul. Śmidowicza 69, 81-127 Gdynia, Poland.

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Summary
This summary is machine-generated.

This study developed process models to monitor the integrity of the Automatic Identification System (AIS), enhancing marine navigation safety. The methods confirmed high integrity for GPS and Dead Reckoning, improving system reliability.

Keywords:
automatic identification systemextended Kalman filterintegrity monitoringreliability theorytrajectory tracking

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Area of Science:

  • Marine Navigation Safety
  • Maritime Surveillance Systems
  • Data Integrity

Background:

  • Existing Automatic Identification System (AIS) faces challenges in sensor data exchange and operational continuity, especially in coastal areas.
  • Littoral AIS availability and coverage gaps necessitate improved system integrity monitoring for reliable marine navigation.
  • Previous research highlighted issues with AIS data quality, impacting its effectiveness in critical maritime operations.

Purpose of the Study:

  • To design and validate process models for simulating vessel trajectories and detecting system failures in AIS.
  • To implement and assess three methods for system integrity monitoring using hypothesis testing against simulated vessel positions.
  • To determine the integrity of AIS information using stochastic methods, specifically Markov chains.

Main Methods:

  • Development of process models for simulating vessel trajectories.
  • Implementation of three integrity monitoring methods: Global Positioning System (GPS) model, Dead Reckoning, and RADAR Extended Kalman Filter (EKF)-Simultaneous Localization and Mapping (SLAM).
  • Validation using simulated AIS dynamic data and stochastic methods based on Markov chains.

Main Results:

  • The proposed integrity monitoring methods were confirmed as useful for enhancing AIS safety.
  • High integrity levels (~99%) were achieved for the dynamic information of the AIS system using Dead Reckoning and GPS process models.
  • The RADAR EKF-SLAM model showed variable accuracy and integrity depending on the proximity to navigational aids.

Conclusions:

  • The developed process models effectively enhance the integrity monitoring of the Automatic Identification System (AIS).
  • GPS and Dead Reckoning models offer high reliability for AIS dynamic information, crucial for safe marine navigation.
  • Further research may be needed to optimize RADAR EKF-SLAM performance in varying navigational aid proximity.