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.

中文翻译：

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基于人工智能的GNSS信号中断期间集成导航系统精度提高的方法：分析概述

摘要—

卡尔曼滤波器（KF）的局限性促使研究人员考虑主要基于人工智能（AI）的惯性导航系统（INS）和全球导航卫星系统（GNSS）集成的替代方法。在过去的二十年中，为了验证在集成导航系统领域使用AI方法的可能性，获得了大量研究。已经提出了用于将AI模块与INS / GNSS系统的其他部分组合的不同方法。本文建议根据INS / GNSS系统中AI模块的功能对结果方案进行新的分类。本文还提供了每种方案的优点和缺点的简要说明。还强调了该领域未来研究中需要考虑的一些方面。