| Title |
Feature Based Extended Target Tracking Using Automotive 2D LIDAR |
| Authors |
함다혜(Dahye Ham) ; 조형찬(Hyung-Chan Cho) ; 윤유정(Yoo-Jung Yoon) ; 나원상(Won-Sang Ra) ; 한슬기(Seul-Ki Han) |
| DOI |
https://doi.org/10.5370/KIEE.2021.70.1.224 |
| Keywords |
Extended target tracking; LIDAR point cloud; Feature extraction; Multiple model filter; UKF |
| Abstract |
This paper deals with the design problem of an extended target tracking filter using automotive 2D LIDAR. As a practical way to reduce the dimensionality of the LIDAR point cloud data and to extract an important target feature from it, the Hough transform is applied and the corresponding measurement equation is modeled. It is well-known that the pattern of the LIDAR point cloud varies with the relative geometry due to occlusion, which may leads the severe performance degradation in target tracking. To cope with this problem, a multiple model filter is designed by considering the measurement acquisition hypotheses on the target feature.
Through the experiments in real-driving condition, the superior performance of the proposed filter over the existing method is demonstrated. |