Journal of Jilin University(Engineering and Technology Edition) ›› 2019, Vol. 49 ›› Issue (5): 1420-1427.doi: 10.13229/j.cnki.jdxbgxb20180673

Previous Articles    

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

Peng-yu WANG1(),Shi-jie ZHAO1,Tian-fei MA1(),Xiao-yong XIONG1,Xin CHENG2   

  1. 1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
    2. School of Information Science and Engineering, Harbin Institute of Technology in Weihai, Weihai 264209, China
  • Received:2018-06-26 Online:2019-09-01 Published:2019-09-11
  • Contact: Tian-fei MA E-mail:16907977@qq.com;matf@jlu.edu.cn

RICH HTML

 22   

PDF (PC)

429

Abstract:

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.

Key words: vehicle engineering, joint probabilistic data association, multi-sensor, target tracking, fusion

CLC Number: 

  • U461.91

Fig.1

Coordinate system"

Fig.2

Logic chart of module of effective target sustained"

Fig.3

Multi-sensor target tracking and fusion algorithm based on modified JPDA"

Fig.4

Scenario of a road experiment"

Table 1

Measure performance of sensors"

设备 测量性能
毫米波雷达 长距模式 距离范围/m:0.20~250 精度/m： ± 0.40 角度范围/(°): ± 9 精度/(°) : ± 0.1
短距模式 距离范围/m : 0.20 ~ 70 精度/m: ± 0.10 角度范围/(°) : ± 45 精度/(°): ± 1.0
速度范围/(km·h): - 400 ~ + 200 精度/(km·h): ± 0.10
摄像头 分辨率: 1280 × 960 像素/M: 1.2 焦距/mm: 5.47
陀螺仪 加速度/g: ± 4 精度/%: ± 1
光电测速仪 速度范围/(km·h): 0.5 ~ 400 精度/%: ± 0.1

卫星

导航

RTK(RMS) 平面/(mm+ppm):10+1 高程/(mm+ppm):15 +1

观测精度(RMS) 码伪距/cm:10 载波相位/mm:1

Fig.5

Comparison of before and after JPDA modified for main target tracking"

Fig.6

Comparison of longitudinal and lateral distance reference values, fusion and state estimation"

Fig.7

Comparison of longitudinal and lateral velocity reference values, fusion and state estimation"

Fig.8

Comparison of longitudinal and lateral acceleration reference values, fusion and state estimation"

Table 2

RMSE of state estimate"

设备 距离/m 速度/(m·s-1) 加速度/(m·s-2)
纵向 侧向 纵向 侧向 纵向 侧向
摄像头 0.1243 0.0918 0.3046 0.4176 0.2149 0.4520
雷达 0.0160 0.0181 0.0469 0.0401 0.0475 0.0338
融合 0.0085 0.0133 0.0195 0.0238 0.0132 0.0163

Fig.9

Comparison of different target tracking algorithms for longitudinal distance"

Table 3

Comparison of different target tracking"

项 目 JPDA MHT EKF+NN
纵向距离/m 0.0085 0.0146 0.0453
侧向距离/m 0.0133 0.0184 0.0489
纵向速度/(m·s-1) 0.0195 0.0220 0.1139
侧向速度/(m·s-1) 0.0238 0.0257 0.1441
纵向加速度/(m·s-1) 0.0132 0.0172 0.1145
侧向加速度/(m·s-1) 0.0163 0.0197 0.0866
计算时间/s 8.7334 12.9186 6.4251
1 Xiao F Y , Qin B . A weighted combination method for conflicting evidence in multi-sensor data fusion[J]. Sensors, 2018, 18(5): 1487-1506.
2 Singer R A , Stein J J . An optimal tracking filter for processing sensor data of imprecisely determined origin in surveillance systems [C]⫽1971 IEEE Conference on Decision and Control, IEEE Miami Beach, 1971: 171-175.
3 Bar-Shalom Y , Tse E . Tracking in a cluttered environment with probabilistic data association[J]. Automatica, 1975, 11(5): 451-460.
4 Chang K C , Bar-Shalom Y . Joint probabilistic data association for multitarget tracking with possibly unresolved measurements and maneuvers[J]. IEEE Transactions on Automatic Control, 1983, 29(7): 585-594.
5 Reid D . An algorithm for tracking multiple targets[J]. IEEE Transactions on Automatic Control, 1978, 24(6): 1202-1211.
6 高振海, 王竣, 佟静, 等 . 车载毫米波雷达对前方目标的运动状态估计[J]. 吉林大学学报: 工学版, 2014, 44(6): 1537-1544.
Gao Zhen-hai , Wang Jun , Tong Jing , et al . Target motion state estimation for vehicle-borne millimeter-wave radar[J]. Journal of Jilin University (Engineering and Technology Edition), 2014, 44(6): 1537-1544.
7 耿峰, 祝小平 . 一种改进的多传感器多目标跟踪联合概率数据关联算法研究[J]. 系统仿真学报, 2007, 19(20): 4671-4675.
Geng Feng , Zhu Xiao-ping . Research of improved joint pro-babilistic data association algorithm for multisensor-multitarget tracking[J]. Journal of System Simulation, 2007, 19(20): 4671-4675.
8 宋晓虹, 陈白帆 . 多传感器信息融合在智能车中的应用研究[J]. 计算机仿真, 2012, 29(6): 320-322, 368.
Song Xiao-hong , Chen Bai-fan . Multi-sensor information fusion in intelligent car[J]. Computer Simulation, 2012, 29(6): 320-322, 368.
9 孙晓峰, 郭徽东 . 异类传感器数据融合系统的模型设计与实现[J]. 舰船电子工程, 2016, 36(7): 47-50.
Sun Xiao-feng , Guo Hui-dong . Model design and application of dissimilar sensor data fusion system[J]. Ship Electronic Engineering, 2016, 36(7): 47-50.
10 周炳玉, 卢野, 刘珍阳 . 多传感器数据融合中的数据预处理技术研究[J]. 红外与激光工程, 2007, 36(增刊2): 246-249.
Zhou Bing-yu , Lu Ye , Liu Zhen-yang . Research on the data preprocessing technique in multi-sensor data fusion system[J]. Infrared and Laser Engineering, 2007,36(Sup.2): 246-249.
11 何友, 高志永 . 多传感器数据融合系统中两种新的航迹相关算法[J]. 电子学报, 1997(9): 10-14.
He You , Gao Zhi-yong . Two new track correlation algorithms in a multisensor data fusion system[J]. Acta Electronica Sinica, 1997(9): 10-14.
12 Chong C Y , Mori S , Barker W H , et al . Architectures and algorithms for track association and fusion[J]. Aerospace & Electronic Systems Magazine IEEE, 2000, 15(1): 5-13.
13 刘卫东, 刘洋, 高立娥 . 基于凸组合和Bar-Shalom-Campo的航迹融合算法研究[J]. 计算机工程与应用, 2014, 50(2): 49-53.
Liu Wei-dong , Liu Yang , Gao Li-e . Research of track fusion based on convex combination and Bar-Shalom-Campo[J]. Computer Engineering and Applications, 2014, 50(2): 49-53.
14 康耀红 . 数据融合理论与应用[M]. 西安: 西安电子科技大学出版社, 1997.
15 Jin B , Guo J , Su B , et al . Adaptive waveform selection for maneuvering target tracking in cognitive radar[J]. Digital Signal Processing, 2018, 75: 210-221.
16 Yuan T , Krishnan K , Chen Q , et al . Object matching for inter-vehicle communication systems——an IMM-based track association approach with sequential multiple hypothesis test[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(12): 3501-3512.
[1] Fang-wu MA,Lu HAN,Yang ZHOU,Shi-ying WANG,Yong-feng PU. Multi material optimal design of vehicle product using polylactic acid composites [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1385-1391.
[2] Zhen-hai GAO,Tian-jun SUN,Lei HE. Causal reasoning decision⁃making for vehicle longitudinal automatic driving [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1392-1404.
[3] Bo ZHANG,Jian-wei ZHANG,Kong-hui GUO,Hai-tao DING,Hong-qing CHU. Current control of permanent magnet synchronous motor for road feeling simulation [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1405-1413.
[4] Xing-jun HU,Zheng HUI,Peng GUO,Yang-hui ZHANG,Jing-long ZHANG,Jing-yu WANG,Fei LIU. Characteristics of aerodynamics for an automobile by fluid-structure coupled method [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1414-1419.
[5] Jing LI,Qiu⁃jun SHI,Peng LIU,Ya⁃wei HU. Neural network sliding mode control of commercial vehicle ABS based on longitudinal vehicle speed estimation [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1017-1025.
[6] Shun YANG,Yuan⁃de JIANG,Jian WU,Hai⁃zhen LIU. Autonomous driving policy learning based on deep reinforcement learning and multi⁃type sensor data [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1026-1033.
[7] Xin CHEN,Ming LI,Xin⁃jian RUAN,Ning WANG,Jia⁃ning WANG. Investigation of vortical structures in wake of Ahmed body by delayed detached⁃eddy simulation turbulence model using immersed boundary method [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1034-1042.
[8] Hua ZHOU,Zhi⁃gang YANG,Hui ZHU. Aerodynamic calculation of MIRA model correlated with wind tunnel test [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1043-1053.
[9] Ji⁃qing CHEN,Meng⁃meng LIU,Feng⁃chong LAN. Experiment on overcharge safety of NCM battery and battery pack [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1072-1080.
[10] Run⁃dong LIU,Jun MAO,Yan⁃hong XI,Hong⁃yu ZHANG,Fei PENG. Pressure pulse on windbreak impacting by cross⁃wind coupling with high⁃speed trains passing each other [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1054-1062.
[11] Guo⁃feng QIN,Jing⁃xin NA,Wen⁃long MU,Wei TAN,Jian⁃ze LUAN,Hao SHEN. Degradation failure of adhesively bonded CFRP/aluminum alloy subjected to high temperature environment [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1063-1071.
[12] Li⁃bin ZHANG,Dao WU,Hong⁃ying SHAN,Xiang⁃jing DENG. Design of axle load self⁃adjusting system for multi⁃axle vehicle based on brake tester [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1081-1091.
[13] Shou⁃tao LI,Qiu⁃yuan LI,Hui LIU,Hui DING,Yan⁃tao TIAN,Ding⁃li YU. Sliding mode variable structure strategy for vehicle stability control [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1288-1292.
[14] Xiong-fei LI,Lu SONG,Xiao-li ZHANG. Remote sensing image fusion based on cooperative empirical wavelet transform [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1307-1319.
[15] Lei CHEN,Jiang⁃feng WANG,Yuan⁃li GU,Xue⁃dong YAN. Multi⁃source traffic data fusion algorithm based onmind evolutionary algorithm optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 705-713.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd