Extended Object Framework based on Weighted Exponential Products

Abstract

Estimating the number of targets and their states is an important aspect of sensor fusion. In some applications, like autonomous driving, multiple measurements stem from extended targets because of multiple reflections from the target’s shape when using high resolution sensors like LiDAR or Radar. Multi-target tracking techniques using point based target assumptions are generally not suitable for these types of sensor measurements. In the last years, a number of techniques have been introduced which use a known shape or estimate the shape to retrieve the position of the object. In this paper we will introduce a novel approach without knowing/estimating the shape but using all the available information by fusing the measurements from one object with a conservative fusion technique based on the Weighted Exponential Product rule. The results show that we obtain similar performance to state-of-the-art approaches in our simulations.