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.

中文翻译：

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汽车雷达信号处理：研究方向和实际挑战

汽车雷达用于高级驾驶辅助系统的许多应用中，被认为是高度自动驾驶的关键技术之一。概述了汽车雷达中最先进的信号处理以及当前的研究方向和实际挑战。我们使用多输入多输出方案为多目标情况提供了一个全面的信号模型，并讨论了一个实际的处理链来计算目标列表。为了展示现代批量生产的高性能雷达传感器的功能，给出了真实的数据示例。概述了机器学习和深度学习方法中的传统目标处理和最近的研究活动。此外，还讨论了用于实际相关的雷达相机融合的最新方法。