Detection and Tracking of a UAV via Hough Transform

被引:0
|
作者
Zhou, Chao [1 ]
Liu, Yang [1 ]
Song, Yuanyuan [1 ]
机构
[1] Beijing Inst Technol, Sch Informat & Elect, Key Lab Embedded Real Time Informat Proc Technol, Beijing, Peoples R China
来源
2016 CIE INTERNATIONAL CONFERENCE ON RADAR (RADAR) | 2016年
关键词
unmanned aerial vehicle; slow small and low targets; target tracking; Hough transform;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Unmanned aerial vehicle (UAV) is a typical low altitude, slow and small (LSS) target. To detect and track this kind of target, a high resolution radar is usually used. In high resolution radar tracking algorithm, scatterers clustering is a key process which has a significant impact on the final performance. However, the lack of theoretical principle for clustering threshold has long been a problem. In this paper, a method based on Hough transform was proposed to improve the detection and tracking performance. By making use of the linear distributed micro Doppler features, the method is able to detect and recognize a UAV simultaneously, thus reduce the limitations on scatterers clustering. Experiment results show that the method can track a UAV continuously and steadily, and improve the tracking accuracy.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] Weeds detection in UAV imagery using SLIC and the Hough transform
    Bah, M. Dian
    Hafiane, Adel
    Canals, Raphael
    PROCEEDINGS OF THE 2017 SEVENTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA 2017), 2017,
  • [2] Power Line Detection and Tracking Using Hough Transform and Particle Filter
    Nasseri, M. H.
    Moradi, H.
    Nasiri, S. M.
    Hosseini, R.
    2018 6TH RSI INTERNATIONAL CONFERENCE ON ROBOTICS AND MECHATRONICS (ICROM 2018), 2018, : 130 - 134
  • [3] Research on Lane Detection and Tracking Algorithm Based on Improved Hough Transform
    Wei, Xianwen
    Zhang, Zhaojin
    Chai, Zongjun
    Feng, Wei
    2018 IEEE INTERNATIONAL CONFERENCE OF INTELLIGENT ROBOTICS AND CONTROL ENGINEERING (IRCE), 2018, : 275 - 279
  • [4] Efficient tracking with the Bounded Hough Transform
    Greenspan, M
    Shang, LM
    Jasiobedzki, P
    PROCEEDINGS OF THE 2004 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 1, 2004, : 520 - 527
  • [5] Based on Hough transform and improved particle filter algorithm for lane detection and tracking
    Xu, Xihai
    Zhou, Yunyao
    Huang, Haibo
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL IX, 2010, : 281 - 284
  • [6] Based on Hough transform and improved particle filter algorithm for lane detection and tracking
    Xu, Xihai
    Zhou, Yunyao
    Huang, Haibo
    2011 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION AND INDUSTRIAL APPLICATION (ICIA2011), VOL IV, 2011, : 280 - +
  • [7] An Eye Tracking Algorithm based on Hough transform
    Bukhalov, Aleksei
    Chafonova, Viktoriia
    2018 INTERNATIONAL SYMPOSIUM ON CONSUMER TECHNOLOGIES (ISCT), 2018, : 49 - 50
  • [8] Lane detection and tracking based on improved Hough transform and least-squares method
    Sun, Peng
    Chen, Hui
    INTERNATIONAL SYMPOSIUM ON OPTOELECTRONIC TECHNOLOGY AND APPLICATION 2014: IMAGE PROCESSING AND PATTERN RECOGNITION, 2014, 9301
  • [9] Integration of Hough Transform and Inter-Frame Clustering for Road Lane Detection and Tracking
    Bisht, Sandeep
    Sukumar, N.
    Sumathi, P.
    2022 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC 2022), 2022,
  • [10] Detection and tracking of coronal mass ejections (CMEs) by means of the watershed segmentation and hough transform
    Nienlewski, Mariusz
    WORLD CONGRESS ON ENGINEERING 2008, VOLS I-II, 2008, : 622 - 628