Automotive Radar Signal Processing: Research Directions and Practical Challenges

Automotive radar is used in many applications of advanced driver assistance systems and is considered as one of the key technologies for highly automated driving. An overview of state-of-the-art signal processing in automotive radar is presented along with current research directions and practical c...

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Vydáno v:IEEE journal of selected topics in signal processing Ročník 15; číslo 4; s. 865 - 878
Hlavní autoři: Engels, Florian, Heidenreich, Philipp, Wintermantel, Markus, Stacker, Lukas, Al Kadi, Muhammed, Zoubir, Abdelhak M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.06.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Advanced driver assistance systems
Automotive electronics
Automotive engineering
Automotive radar
autonomous vehicles
Deep learning
Machine learning
MIMO
MIMO radar
Production
Radar applications
Radar signal processing
Signal processing
State-of-the-art reviews
ISSN:1932-4553, 1941-0484
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Popis
Shrnutí:Automotive radar is used in many applications of advanced driver assistance systems and is considered as one of the key technologies for highly automated driving. An overview of state-of-the-art signal processing in automotive radar is presented along with current research directions and practical challenges. We provide a comprehensive signal model for the multiple-target case using multiple-input multiple-output schemes, and discuss a practical processing chain to calculate the target list. To demonstrate the capabilities of a modern series production high-performance radar sensor, real data examples are given. An overview of conventional target processing and recent research activities in machine learning and deep learning approaches is presented. Additionally, recent methods for practically relevant radar-camera fusion are discussed.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1932-4553
1941-0484
DOI:10.1109/JSTSP.2021.3063666