Modified extended object tracker for 2D lidar data using random matrix model

The random matrix (RM) model is a typical extended object-modeling method that has been widely used in extended object tracking. However, existing RM-based filters usually assume that the measurements follow a Gaussian distribution, which may lead to a decrease in accuracy when the filter is applied...

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Bibliographic Details
Published in:Scientific reports 2023-03, Vol.13 (1), p.5095-5095, Article 5095
Main Authors: Li, Peng, Chen, Cheng, You, Cong-zhe, Qiu, Jun-da
Format: Article
Language:English
Subjects:
639/166/984
639/705/117
639/705/258
Humanities and Social Sciences
Kinematics
Lidar
multidisciplinary
Normal distribution
Science
Science (multidisciplinary)
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Summary:The random matrix (RM) model is a typical extended object-modeling method that has been widely used in extended object tracking. However, existing RM-based filters usually assume that the measurements follow a Gaussian distribution, which may lead to a decrease in accuracy when the filter is applied to the lidar system. In this paper, a new observation model used to modify an RM smoother by considering the characteristics of 2D LiDAR data is proposed. Simulation results show that the proposed method achieves a better performance than the original RM tracker in a 2D lidar system.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-32236-w