Deep Learning Methods for Automotive Radar Signal Processing.

Intro -- 1 Introduction -- 1.1 Goals and Contents of this Work -- 2 Radar Fundamentals -- 2.1 Continuous Wave Radar -- 2.2 Mono-Frequent Continuous Wave Radar -- 2.3 Linear Frequency Modulated Continuous WaveRadar -- 2.4 Chirp Sequence Frequency Modulated ContinuousWave Radar -- 2.5 Target Detection -- 2.6 Phased Arrays -- 2.7 Radar System Considerations -- 3 Machine Learning Fundamentals -- 3.1 Supervised Learning -- 3.2 Artificial Neural Networks -- 3.3 Training of Artificial Neural Networks -- 3.5 Loss Functions -- 3.6 Evaluation Metrics -- 4 Classification of Vulnerable RoadUsers -- 4.1 The Micro-Doppler Effect -- 4.2 Single Frame Vulnerable Road Users Classification -- 4.3 Joint Lidar and Radar Classification System -- 4.4 Concluding Remarks -- 5 Deep Learning Based Radar TargetDetection -- 5.1 Detection in Frequency Domain -- 5.2 Time Domain Detection -- 5.3 Concluding Remarks -- 6 Conclusion -- 6.1 Outlook -- Symbols -- Acronyms -- Bibliography -- Own Publications.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.