Kayak Tracking using a Direct Lidar Model

Abstract

This paper proposes a direct approach for extended object tracking (EOT) using light detection and ranging (lidar) measurements. The method does not use any clustering operations, but processes the individual laser beams directly in an extended Kalman filter (EKF), and resolves data association by means of techniques reminiscent of the probabilistic data association filter (PDAF). The method is particularly tailored to tracking of kayaks, and parameterizes the shape of the kayak as a stick whose length is part of the state vector. The proposed method is evaluated through a simulation study and tested on real lidar data.