Model-Based Parameter Estimation in Automotive Radar Signal Processing

mm-Wave radar is considered as one of the enabling technologies for autonomous driving (AD). Compared to advanced driver assistance systems, AD implies strongly increased demands on resolution, accuracy, field of view, false positive rates, and true positive rates. To meet these demands, not only system level approaches, such as adapted modulations, optimized antenna arrays, and MIMO schemes, but also advanced signal processing strategies, such as machine learning, compressed sensing, and model-based parameter estimation, are actively developed. In this workshop, we give an overview of model-based parameter estimation applied in automotive radar signal processing. In particular, we will cover high-resolution range, velocity, direction estimation, MIMO radar angle estimation in the presence of multipath, and MIMO radar false-alarm suppression.