Indoor Navigation Using Wireless Localization Techniques

Indoor Navigation Using Wireless Localization Techniques

Indoor Infrared Optical Wireless Communications

This book aims to give an overview of recent developments in indoor near-infrared optical wireless communication technologies and systems, including basic theories, operating fundamentals, system architectures, modelling, experimental demonstrations, advanced techniques, and most recently, the research efforts towards integrations. Both line-of-sight and diffusive-signals-based options will be reviewed, to provide readers a complete picture about this rapidly developing area, which targets the provision of high-speed wireless connectivity to end- users in indoor environments, such as offices, homes and shopping centres, to satisfy the growing high-speed communication requirement. Provides a systematic approach for the fundamentals of indoor optical wireless communications. Provides an overview of recent developments in indoor infrared optical wireless communications, including theoretical fundamentals. Examines system architectures, modelling, experimental demonstrations, and the research efforts towards integrations. Dr. Ke Wang is an Australian Research Council (ARC) DECRA Fellow and a senior lecturer in the School of Engineering, Royal Melbourne Institute of Technology (RMIT University), VIC, Australia. He worked with the University of Melbourne, Australia, and Stanford University, California, before joining RMIT University. He has published over 110 peer-reviewed papers in top journals and leading international conferences, including over 20 invited papers. He has been awarded several prestigious national and international awards as recognition of research contributions, such as the Victoria Fellowship, the AIPS Young Tall Poppy Science Award, and the Marconi Society Paul Baran Young Scholar Award. His major areas of interest include: silicon photonics integration, opto-electronics integrated devices and circuits, nanophotonics, optical wireless technology for short-range applications, quasi-passive reconfigurable devices and applications and optical interconnects in data -centres and high-performance computing.

Positioning and Navigation Using Machine Learning Methods

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.