Discriminating Distributed Targets in Automotive Radar Using Fuzzy L-Shell Clustering Algorithm

被引:0
作者
Ren, Zhouchang [1 ,2 ]
Tabrikian, Joseph [1 ]
Bilik, Igal [1 ]
Yi, Wei [2 ]
机构
[1] Ben Gurion Univ Negev, Sch Elect & Comp Engn, IL-8410501 Beer Sheva, Israel
[2] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Peoples R China
基金
以色列科学基金会; 中国国家自然科学基金;
关键词
Radar; Automotive engineering; Radar detection; Vectors; Shape; Reliability; Radar scattering; Automotive radar; distributed targets; fuzzy shell clustering; target discrimination; target enumeration;
D O I
10.1109/TAES.2024.3435808
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Automotive radar is the commonly used sensor for autonomous driving and active safety. Modern automotive radars provide high spatial information on the host vehicle surroundings, and therefore, automotive radar targets appear as point clouds of radar detections. This article addresses the problem of discriminating between adjacent distributed targets using the distribution of radar detections in the range-azimuth domain. The proposed approach considers both the statistical information of the radar detections' distribution and the L-shape model of the target vehicles via the fuzzy L-shell clustering algorithm. The performance of the proposed approach is evaluated via simulations, and its superiority over the conventional methods is demonstrated in practical automotive scenarios.
引用
收藏
页码:8713 / 8725
页数:13
相关论文
共 39 条
  • [1] [Anonymous], 1997, Learning, Networks and Statistics
  • [2] A new possibilistic clustering algorithm for line detection in real world imagery
    Barni, M
    Gualtieri, R
    [J]. PATTERN RECOGNITION, 1999, 32 (11) : 1897 - 1909
  • [3] Target detection and localization using. MIMO radars and sonars
    Bekkerman, Ilya
    Tabrikian, Joseph
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2006, 54 (10) : 3873 - 3883
  • [5] The Rise of Radar for Autonomous Vehicles Signal processing solutions and future research directions
    Bilik, Igal
    Longman, Oren
    Villeval, Shahar
    Tabrikian, Joseph
    [J]. IEEE SIGNAL PROCESSING MAGAZINE, 2019, 36 (05) : 20 - 31
  • [6] Bilik I, 2018, IEEE RAD CONF, P372, DOI 10.1109/RADAR.2018.8378587
  • [7] Bilik I, 2016, IEEE RAD CONF, P788
  • [8] A Novel Density Peak Fuzzy Clustering Algorithm for Moving Vehicles Using Traffic Radar
    Cao, Lin
    Liu, Yunxiao
    Wang, Dongfeng
    Wang, Tao
    Fu, Chong
    [J]. ELECTRONICS, 2020, 9 (01)
  • [9] Cao XM, 2018, 2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), P1738, DOI 10.23919/ICIF.2018.8455293
  • [10] Chakrabarti A, 2011, HBK PHILOS SCI, V7, P583