Positioning and Navigation Using Machine Learning Methods
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Beschreibung
This is the first book completely dedicated to positioning and navigation using machine learning methods. It deals with ground, aerial, and space positioning and navigation for pedestrians, vehicles, UAVs, and LEO satellites. Most of the major machine learning methods are utilized, including supervised learning, unsupervised learning, deep learning, and reinforcement learning. The book presents both fundamentals and in-depth studies as well as practical examples in positioning and navigation. Extensive data processing and experimental results are provided in the major chapters through conducting experimental campaigns or using in-situ measurements.
This is the first book completely dedicated to positioning and navigation using machine learning methods. It deals with ground, aerial, and space positioning and navigation for pedestrians, vehicles, UAVs, and LEO satellites. Most of the major machine learning methods are utilized, including supervised learning, unsupervised learning, deep learning, and reinforcement learning. The book presents both fundamentals and in-depth studies as well as practical examples in positioning and navigation. Extensive data processing and experimental results are provided in the major chapters through conducting experimental campaigns or using in-situ measurements.
Provides a comprehensive treatment of theory and practice of positioning and navigation based on machine learning Exploits a range of machine learning methods for positioning and navigation Considers different application scenarios, namely ground, air and space, and different types of users
Autor*in
Kegen Yu
Themen in »Positioning and Navigation Using Machine Learning Methods«
Positioning and navigation Machine learning deep learning reinforcement learning distributed learning pedestrian positioning vehicle positioning UAV positioning and navigation planetary rover positioning and navigation