Joint Tracking and Identification Based on Constrained Joint Decision and Estimation

被引:4
|
作者
Cao, Wen [1 ]
Lan, Jian [2 ]
Wu, Qisheng [1 ]
机构
[1] Changan Univ, Sch Elect & Control Engn, Xian 710064, Peoples R China
[2] Xi An Jiao Tong Univ, Ctr Informat Engn Sci Res CIESR, Sch Elect & Informat Engn, Xian 710049, Peoples R China
基金
中国国家自然科学基金;
关键词
Target tracking; Roads; Estimation; Automobiles; Couplings; Mathematical model; Joint tracking and identification; constrained estimation; joint decision and estimation; joint performance metric; TARGET TRACKING; LANE IDENTIFICATION; VIOLATION DETECTION; EXTENDED-OBJECT; ROAD; PERFORMANCE; RADAR;
D O I
10.1109/TITS.2020.2992637
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
As a critical component of traffic safety, violation detection and treatment can effectively reduce illegal driving so as to ensure the safety of our lives. In this system, both road-constrained target tracking and identification are involved, which are coupled. This is a constrained joint tracking and identification (CJTI) problem, and good solutions require addressing the two problems jointly. The recently proposed joint decision and estimation (JDE) framework and the conditional JDE (CJDE) approach have been proved to be superior for such problems involving coupled decision (identification) and estimation (tracking). Inspired by this, for CJTI of ground targets, this paper proposes a novel constrained CJDE approach. First, a hybrid CJTI system incorporating target dynamics, class characteristics and road constraints is formulated. Based on this, we propose a constrained CJDE risk converting a constrained tracking cost and a constrained identification risk into one framework. An optimal constrained CJDE solution containing an estimator and a decider is derived. Simulation results verify the effectiveness of the proposed constrained CJDE method. They show that by fully utilizing the constraint information and the coupling between tracking and identification, the constrained CJDE approach outperforms traditional two-step methods in joint performance.
引用
收藏
页码:6489 / 6502
页数:14
相关论文
共 50 条
  • [1] Joint Tracking for Capturing and Classification Based on Joint Decision and Estimation
    Ji, Qingqiang
    Lan, Jian
    Li, X. Rong
    [J]. 2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2018, : 2121 - 2128
  • [2] Joint tracking and classification based on Bayes joint decision and estimation
    Li, X. Rong
    Yang, Ming
    Ru, Jifeng
    [J]. 2007 PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4, 2007, : 1431 - +
  • [3] Joint Tracking and Classification Based on Conditional Joint Decision and Estimation
    Cao, Wen
    Lan, Jian
    Li, X. Rong
    [J]. 2015 18TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2015, : 1764 - 1771
  • [4] Compact Conditional Joint Decision and Estimation for Joint Tracking and Identification With Performance Evaluation
    Cao, Wen
    Hui, Meng
    Bai, Lin
    Yao, Bobin
    [J]. IEEE ACCESS, 2018, 6 : 4395 - 4404
  • [5] Multi-target joint tracking and classification based on joint decision and estimation
    Zhang, Xue
    Li, Minzhe
    [J]. SIGNAL IMAGE AND VIDEO PROCESSING, 2024, 18 (10) : 6891 - 6901
  • [6] Joint Fault Detection, Identification, and State Estimation Based on Conditional Joint Decision and Estimation
    Ji, Qingqiang
    Lan, Jian
    Li, X. Rong
    [J]. 2016 19TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2016, : 1147 - 1154
  • [7] Conditional Joint Decision and Estimation With Application to Joint Tracking and Classification
    Cao, Wen
    Lan, Jian
    Li, X. Rong
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 46 (04): : 459 - 471
  • [8] Constrained Testing and Estimation for Bayesian Joint Decision and Estimation
    Gao, Yongxin
    Song, Enbin
    Li, X. Rong
    [J]. 2016 19TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2016, : 1284 - 1291
  • [9] Extended Object Tracking and Classification based on Recursive Joint Decision and Estimation
    Cao, Wen
    Lan, Jian
    Li, X. Rong
    [J]. 2013 16TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2013, : 1670 - 1677
  • [10] A novel joint multi-target detection and tracking approach based on Bayes joint decision and estimation
    Cao, Wen
    Li, Qiwei
    [J]. EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2023, 2023 (01)