Machine-Learning-Based Positioning: A Survey and Future Directions
IEEE Network(2019)
摘要
Widespread use of mobile intelligent terminals has greatly boosted the application of location-based services over the past decade. However, it is known that traditional location- based services have certain limitations such as high input of manpower/material resources, unsatisfactory positioning accuracy, and complex system usage. To mitigate these issues, machinelearning- based location services are currently receiving a substantial amount of attention from both academia and industry. In this article, we provide a retrospective view of the research results, with a focus on machine-learning-based positioning. In particular, we describe the basic taxonomy of location-based services and summarize the major issues associated with the design of the related systems. Moreover, we outline the key challenges as well as the open issues in this field. These observations then shed light on the possible avenues for future directions.
更多查看译文
关键词
Deep learning,Satellite broadcasting,Training,Global Positioning System,Wireless fidelity,Radio navigation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络