Radar Signal Processing for Autonomous Driving

1. Auflage 2020
ISBN: 978-981-13-9195-8
Verlag: Springer Nature Singapore

Buch, Englisch, 142 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 254 g

Reihe: Signals and Communication Technology

The subject of this book is theory, principles and methods used in radar algorithm development with a special focus on automotive radar signal processing. In the automotive industry, autonomous driving is currently a hot topic that leads to numerous applications for both safety and driving comfort. It is estimated that full autonomous driving will be realized in the next twenty to thirty years and one of the enabling technologies is radar sensing. This book presents both detection and tracking topics specifically for automotive radar processing. It provides illustrations, figures and tables for the reader to quickly grasp the concepts and start working on practical solutions. The complete and comprehensive coverage of the topic provides both professionals and newcomers with all the essential methods and tools required to successfully implement and evaluate automotive radar processing algorithms.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Gamba, Jonah

Fachgebiete

• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Fundamentals of Radar Systems.- The Radar Equation.- Signal Processing for Radar Systems.- Radar Waveforms and Their Mathematical Models.- Radar Target Detection.- Direction of Arrival (DOA) Estimation.- Target Filtering and Tracking.- Automotive Radar Applications.

Über Autor(innen)

Jonah Gamba received a BSc degree in Electrical and Electronics Engineering from the University of Zimbabwe in 1994 and an MSc in Computer Science and Engineering from Zhejiang University, Hangzhou, China, in 2000. He obtained a PhD degree in Mathematical Information Systems from Saitama University in 2005. He was a post-doctoral research fellow in information theory at Tsukuba University from 2006 to 2008.
He has been actively involved in research and development activities after obtaining his PhD. He conducted research in automotive applications of millimeter-wave radar for advanced vehicle safety and comfort systems. At Tsukuba University’s Tsukuba Advanced Research Alliance he conducted research in video and image processing algorithms as a JST CREST Project postdoctoral researcher. CREST is the highest level of research in Japan. His research activities involved development of the next generation high resolution algorithms for both high definition TVs and portable mobile devices such as smartphones. In application area, he was key part model based development activities in signal processing, communications and physical modeling as an Application Engineer. His main task was to implementing signal processing and control algorithms for the automotive and electronics industry clients. This area targeted both hardware and software development especially DSPs and FPGA/ASIC. Additionally, he was a software R&D engineer and manager for multicore/many-core microprocessors deployed in automotive vision, video mining and mobile applications. His task is to manage and develop software for multicore processors with the aim of increasing performance while minimizing energy consumption. He was also a leading developer of the millimeter wave radar sensor for autonomous driving applications with Fujitsu Ten.
Dr. Gamba has authored and co-authored several publications in signal processing and related fields. As an inventor, he has registeredmultiple patents in signal processing applications. His current interests are signal processing for automotive applications, functional safety management and remote sensing. He has been a visiting researcher of Seikei University and Tokyo University. He is a member of IEEE Signal Processing Society.