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Multi-Target Tracking Algorithm Combined with High-Precision Map
DOI:10.3390/s22239371.png)
摘要
En 中文
On high-speed roads, there are certain blind areas within the radar coverage, especially when the blind zone is in curved road sections; because the radar does not have the measurement point information in multiple frames, it is easy to have a large deviation between the real trajectory and the filtered trajectory. In this paper, we propose a track prediction method combined with a high-precision map to solve the problem of scattered tracks when the targets are in the blind area. First, the lane centerline is fitted to the upstream and downstream lane edges obtained from the high-precision map in certain steps, and the off-north angle at each fitted point is obtained. Secondly, the normal trajectory is predicted according to the conventional method; for the extrapolated trajectory, the northerly angle of the lane centerline at the current position of the trajectory is obtained, the current coordinate system is converted from the north-east-up (ENU) coordinate system to the vehicle coordinate system, and the lateral velocity of the target is set to zero in the vehicle coordinate system to reduce the error caused by the lateral velocity drag of the target. Finally, the normal trajectory is updated and corrected, and the normal and extrapolated trajectories are managed and reported. The experimental results show that the accuracy and convergence effect of the proposed methods are much better than the traditional methods.
Keyword:
FMCW radar
high-precision map
Kalman filtering
data association
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期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
Lane-by-Lane Traffic Monitoring Using 24.1 GHz FMCW Radar System使用24.1 GHz FMCW雷达系统进行逐车道交通监控
IEEE ACCESS
IF3.6
Tracking all traffic - Computer vision algorithms for monitoring vehicles, individuals, and crowds跟踪所有交通-用于监控车辆,个人和人群的计算机视觉算法

