Learning-based Extended Object Tracking Using Hierarchical Truncation Measurement Model with Automotive Radar
This paper presents a data-driven measurement model for extended object tracking (EOT) with automotive radar. Specifically, the spatial distribution of automotive radar measurements is modeled as a hierarchical truncated Gaussian (HTG) with structural geometry parameters, e.g., truncation bounds, orientation, and scaling, that can be learned from the training data. The HTG measurement model provid