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Artificial Intelligence Based Methods for Accuracy Improvement of Integrated Navigation Systems During GNSS Signal Outages: An Analytical Overview

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Abstract—

The limitations of Kalman filter (KF) have motivated researchers to consider alternative methods of integrating inertial navigation systems (INS) and global navigation satellite systems (GNSS), predominantly based on artificial intelligence (AI). Over the past two decades, a great number of research gained in order to validate the possibility of using AI methods in the field of integrated navigation systems. Different approaches have been proposed for combining AI modules with the other parts of the INS/GNSS system. The article suggests a new classification of the resulting schemes based on the functionality of AI modules in the INS/GNSS system. The paper also provides a brief explanation of each scheme with its advantages and disadvantages. Some aspects that need to be considered in future research in this field are also highlighted.

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Authors and Affiliations

  1. Department of Automatic Control Systems, Bauman Moscow State Technical University (BMSTU), Moscow, Russia

    Nader Al Bitar & Alexander Gavrilov

  2. Department of Electronic & Mechanical Systems, Higher Institute for Applied Sciences and Technology (HIAST), Damascus, Syria

    Wassim Khalaf

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  1. Nader Al Bitar
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  2. Alexander Gavrilov
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  3. Wassim Khalaf
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Correspondence to Nader Al Bitar, Alexander Gavrilov or Wassim Khalaf.

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Nader Al Bitar, Gavrilov, A. & Khalaf, W. Artificial Intelligence Based Methods for Accuracy Improvement of Integrated Navigation Systems During GNSS Signal Outages: An Analytical Overview. Gyroscopy Navig. 11, 41–58 (2020). https://doi.org/10.1134/S2075108720010022

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  • DOI: https://doi.org/10.1134/S2075108720010022

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