Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (7): 2104-2114.doi: 10.13229/j.cnki.jdxbgxb.20221174

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Target recognition and tracking of group vehicles based on roadside millimeter-wave radar

Li LI1(),Xiao-qiang WU1,Wen-chen YANG2,3,Rui-jie ZHOU1,Gui-ping WANG1()   

  1. 1.School of Electronic and Control Engineering，Chang'an University，Xi'an 710064，China
    2.National Engineering Laboratory for Surface Transportation Weather Impacts Prevention，Broadvision Engineering Consultants Co. ，Ltd，Kunming 650200，China
    3.Yunnan Key Laboratory of Digital Communications，Kunming 650103，China
  • Received:2022-09-11 Online:2024-07-01 Published:2024-08-05
  • Contact: Gui-ping WANG E-mail:lili@chd.edu.cn;gpwang@chd.edu.cn

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Abstract:

A method of group vehicle recognition and tracking based on roadside millimetre-wave radar was proposed to improve roadway traffic detection accuracy. Based on pre-processed detection data of millimetre-wave radar on multi-lane traffic flow in an urban arterial road， a Gaussian kernel-distance based spatial clustering algorithm with noise density （DBSCAN） was proposed to conduct spatio-temporal clustering of effective radar signals reflected by group vehicles. Then， a fusion algorithm of unscented Kalman filter （UKF） and linear Gaussian mixture probability hypothesis density （GMPHD） was proposed to improve tracking accuracy of group vehicles which move nonlinearly on the road. The algorithms were tested in simulation and onsite environment. Simulation results verified that the UK-GMPHD algorithm can accurately and stably track nonlinear moving vehicles. Results of onsite test showed that the kernel-distance based DBSCAN algorithm can solve the problem of classical algorithm effectively that the parameter tuning of feature vector was difficult to adjust. The UK-GMPHD algorithm reduced the root mean square error of target tracking in term of target distance， velocity and angle by 21.03%， 23.41% and 20.67% in comparison with GMPHD algorithm.

Key words: intelligent transportation, millimeter wave radar, group vehicles, target recognition, vehicle tracking, filter, Gaussian mixture probability hypothesis density

CLC Number: 

  • TN953

Table 1

Parameters of millimeter wave radar"

参数短距长距
距离测量/m0.2~700.2~250
距离精度/m±0.1±0.4
测速范围/（km·h-1）-400~+200（-为远离，+为接近）-400~+200（-为远离，+为接近）
速度精度/（km·h-1）±0.1±0.1
方位角/（°）-60~+60-9~+9

Fig.1

Diagram of data collection"

Table 2

Data frame of millimeter wave radar"

信号含义符号单位
目标编号ID—
纵向距离（X轴方向）Rxm
横向距离（Y轴方向）Rym
纵向速度（X轴方向）vxm/s
横向速度（Y轴方向）vym/s
目标反射截面SrcsdBm2

Fig.2

Frequency histogram of target motion parameters"

Fig.3

UK-GMPHD algorithm process"

Fig.4

Comparison of target recognition algorithms"

Fig.5

Average OSPA distance under different target detection probabilities"

Fig.6

Target tracking simulation results"

Fig.7

Target tracking performance comparison"

Table 3

Comparison of algorithm performance"

目标参数GMPHD算法UK-GMPHD算法误差减少量
距离4.536 m3.582 m21.03%
速度1.162 m/s0.89 m/s23.41%
角度1.432°1.136°20.67%

Fig.8

Driving scene， measured data and vehicle tracking results"

Fig.9

GMPHD and UK-GMPHD algorithm comparison chart"

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