TY  - BOOK
AU  - Yu,Kegen
ED  - SpringerLink (Online service)
TI  - Positioning and Navigation Using Machine Learning Methods
T2  - Navigation: Science and Technology,
SN  - 9789819761999
AV  - TK5101-5105.9 
U1  - 621.382 23
PY  - 2024///
CY  - Singapore
PB  - Springer Nature Singapore, Imprint: Springer
KW  - Telecommunication
KW  - Machine learning
KW  - Signal processing
KW  - Communications Engineering, Networks
KW  - Machine Learning
KW  - Signal, Speech and Image Processing
N1  - Chapter 1. Introduction -- Chapter 2. Indoor localization using ranging model constructed with BP neural network -- Chapter 3. Classification of signal propagation channel using CNN and wavelet packet analysis -- Chapter 4. Semi supervised indoor localization -- Chapter 5. Unsupervised learning for practical indoor localization -- Chapter 6. Deep learning based PDR localization using smartphone sensors and GPS data -- Chapter 7. Deductive reinforcement learning for vehicle navigation -- Chapter 8. Privacy preserving aggregation for federated learning based navigation -- Chapter 9. Learning enhanced INS/GPS integrated navigation -- Chapter 10. UAV localization using deep supervised learning and reinforcement learning -- Chapter 11. Learning based UAV path planning with collision avoidance -- Chapter 12. Learning assisted navigation for planetary rovers -- Chapter 13. Improved planetary rover localization using slip based autonomous ZUPT
N2  - 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
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-97-6199-9
ER  -