Automotive Radar Signal Processing: Research Directions and Practical Challenges
| Autor: | Markus Wintermantel, Florian Engels, Philipp Heidenreich, Muhammed Al Kadi, Abdelhak M. Zoubir, Lukas Stäcker |
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| Rok vydání: | 2021 |
| Předmět: |
Signal processing
Computer science business.industry Deep learning 020206 networking & telecommunications Advanced driver assistance systems 02 engineering and technology Series production Signal Radar engineering details Automotive radar Signal Processing 0202 electrical engineering electronic engineering information engineering Key (cryptography) Systems engineering Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | IEEE Journal of Selected Topics in Signal Processing. 15:865-878 |
| ISSN: | 1941-0484 1932-4553 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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