Random Matrix-based Tracking of Rectangular Extended Objects with Contour Measurements

A widely-used approach for extended object tracking is based on random matrices, where the scattering matrix, i.e., measurement spread, is used to update a symmetric positive definite random matrix representing an elliptic extent. However, for lidar data, a mismatch between the assumed measurement model and observed data hinders the estimation quality of the method. We propose adaptions to the random matrix approach in order to facilitate the application for tracking a rectangular extended object based on contour measurements. Specifically, we derive a suitable scaling factor for the scattering matrix of measurements in this setting. Furthermore, we propose a simple yet effective estimation scheme for the target center, adapting the shape estimate accordingly. The resulting algorithm closely follows the framework of the random matrix approach. A detailed comparison with a variety of state-of-the-art trackers is carried out in a simulation based on real-world lidar parameters, confirming the effectiveness of the approach.