Extended Target Tracking with a Particle Filter Using State Dependent Target Measurement Models

This paper presents an extended object tracking algorithm. We model visibility constraints in the measurement process. A sequential importance sampling and resampling particle filter is used, which permits a flexible modeling of the target shape. We compare our method to the standard approach of just rotating and translating the target extent model. Our approach is applicable for both radar and LiDAR sensors. Results are presented in a a simulated scenario with LiDAR data. A proof of concept is conducted in a real world scenario with radar data.