Litcius/Paper detail

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

N. Al Bitar, Alexander I. Gavrilov, Wassim Khalaf

2020Gyroscopy and Navigation33 citationsDOI

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.

Topics & Concepts

GNSS applicationsComputer scienceInertial navigation systemKalman filterSatellite systemField (mathematics)GNSS augmentationNavigation systemSystems engineeringArtificial intelligenceSatellite navigationGlobal Positioning SystemReal-time computingEngineeringTelecommunicationsInertial frame of referencePhysicsPure mathematicsMathematicsQuantum mechanicsInertial Sensor and NavigationGNSS positioning and interferenceTarget Tracking and Data Fusion in Sensor Networks