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

被引：17

作者：

Nader Al Bitar ^{[1
]}

Gavrilov A. ^{[1
]}

Khalaf W. ^{[2
]}

机构：

[1] Department of Automatic Control Systems, Bauman Moscow State Technical University (BMSTU), Moscow

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

来源：

Gyroscopy and Navigation | 2020年 / 11卷 / 01期

关键词：

artificial intelligence; global navigation satellite systems; Inertial navigation systems; Kalman filter; neural networks;

D O I：

10.1134/S2075108720010022

中图分类号：

学科分类号：

摘要：

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. © 2020, Pleiades Publishing, Ltd.

引用

页码：41 / 58

页数：17

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