Vehicle multi-sensor target tracking and fusion algorithm based on joint probabilistic data association

被引：0

作者：

Wang P.-Y. ^{[1
]}

Zhao S.-J. ^{[1
]}

Ma T.-F. ^{[1
]}

Xiong X.-Y. ^{[1
]}

Cheng X. ^{[2
]}

机构：

[1] State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun

[2] School of Information Science and Engineering, Harbin Institute of Technology in Weihai, Weihai

来源：

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2019年 / 49卷 / 05期

关键词：

Fusion; Joint probabilistic data association; Multi-sensor; Target tracking; Vehicle engineering;

D O I：

10.13229/j.cnki.jdxbgxb20180673

中图分类号：

学科分类号：

摘要：

To solve the problem of intelligent vehicle forward multi-sensor multi-target tracking and fusion, an algorithm of vehicle multi-sensor target tracking and fusion based on modified joint probabilistic data association is proposed. First, according to the relative motion of the vehicle coordinate system and sensor coordinate system, the multi-sensor data is transformed. Then, the single-sensor multi-target tracking based on modified joint probabilistic data association, the multi-sensor track correlation based on correlation sequential track association and convex combination fusion are adopted to achieve stable tracking and accurate fusion of the target. Finally, the experimental vehicle equipped with millimeter-wave radar and camera is tested in actual traffic environment. The results show that the target is tracked steadily and the fusion results have good accuracy which verify the feasibility and effectiveness of the proposed algorithm. © 2019, Jilin University Press. All right reserved.

引用

页码：1420 / 1427

页数：7

共 15 条

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