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低慢小飞行物实时检测原理与实验研究

于凯洋 张磊 王克逸

于凯洋, 张磊, 王克逸. 低慢小飞行物实时检测原理与实验研究[J]. 应用光学.
引用本文: 于凯洋, 张磊, 王克逸. 低慢小飞行物实时检测原理与实验研究[J]. 应用光学.
YU Kaiyang, ZHANG Lei, WANG Keyi. Real-time detection principle and experimental study of low and slow small flying objects[J]. Journal of Applied Optics.
Citation: YU Kaiyang, ZHANG Lei, WANG Keyi. Real-time detection principle and experimental study of low and slow small flying objects[J]. Journal of Applied Optics.

低慢小飞行物实时检测原理与实验研究

基金项目: 国家自然科学基金(61935008)
详细信息
    作者简介:

    于凯洋(1997—),男,硕士研究生,主要从事FPGA视频图像处理技术研究。E-mail:ykaiyang@mail.ustc.edu.cn

    通讯作者:

    王克逸(1962—),男,博士,博士生导师,教授,主要从事光电系统、微光学与信息光学技术研究。E-mail:kywang@ustc.edu.cn

  • 中图分类号: TN02;TP277

Real-time detection principle and experimental study of low and slow small flying objects

  • 摘要: 飞鸟撞击飞机与无人机黑飞是威胁航班起降安全的两大隐患,上述的飞鸟和无人机都属于“低慢小”飞行物。为保卫机场净空区的安全,需要研制具有反低慢小功能的预警系统。对此,设计并实现了一套低慢小飞行物实时检测系统,基于FPGA(field programmable gate array)驱动相机阵列实时采集大视场天空视频,将适于硬件操作的奇偶分流算法与帧间差分算法相结合进行运动目标检测,系统帧率达到17 fps@1 024×768 pixel,平均检测准确率为99.69%。采用千兆以太网、光纤和交换机将前端跑道视频传输至后端塔台指挥中心,支持3 km远距离传输。相比于传统基于软件串行处理的方式,该系统具有高实时性、低功耗与小体积的优势,适合部署在实际应用场景中。
  • 图  1  系统整体设计方案

    Fig.  1  Overall system design solution

    图  2  运动目标检测算法流程

    Fig.  2  Motion target detection algorithm flow

    图  3  FPGA中值滤波

    Fig.  3  FPGA median filtering

    图  4  帧间差分仿真图

    Fig.  4  Inter-frame differential simulation diagram

    图  5  系统实物图

    Fig.  5  System physical diagram

    图  6  运动目标检测结果

    Fig.  6  Motion target detection results

    图  7  LCD屏人机交互界面

    Fig.  7  LCD screen human-machine interaction interface

    表  1  检测准确率评价结果

    Table  1  Detect accuracy evaluation results %

    评价指标最大值最小值中值平均值
    Edrel2.497 40.091 60.883 40.875 8
    RFP2.663 70.000 00.060 90.134 4
    RFN1.239 60.000 00.093 20.141 4
    PWC2.692 20.025 40.184 80.267 6
    RSP100.000 097.336 399.939 199.865 6
    下载: 导出CSV

    表  2  不同平台性能对比

    Table  2  Different platform performance comparison

    平台帧率/fps功耗/W尺寸/(cm3
    双FPGA1719.7216.04×11.57×7.26
    PC机465.0946.72×18.76×43.45
    下载: 导出CSV
  • [1] 王维, 项洪达. 鸟击风险计算方法研究[J]. 中国民航大学学报,2019,37(5):21-24. doi: 10.3969/j.issn.1674-5590.2019.05.005

    WANG Wei, XIANG Hongda. Research on the calculation method of bird strike risk[J]. Journal of Civil Aviation University of China,2019,37(5):21-24. doi: 10.3969/j.issn.1674-5590.2019.05.005
    [2] FLOREANO D, WOOD R J. Science, technology and the future of small autonomous drones[J]. Nature,2015,521(7553):460-466. doi: 10.1038/nature14542
    [3] 张建伟, 郭会明. 低空慢速小目标拦截系统研究[J]. 计算机工程与设计,2012,33(7):2874-2878. doi: 10.3969/j.issn.1000-7024.2012.07.067

    ZHANG Jianwei, GUO Huiming. Research on low altitude slow speed small target interception system[J]. Computer Engineering and Design,2012,33(7):2874-2878. doi: 10.3969/j.issn.1000-7024.2012.07.067
    [4] SHI X, YANG C, XIE W, et al. Anti-drone system with multiple surveillance technologies: architecture implementation and challenges[J]. IEEE Communications Magazine,2018,56(4):68-74. doi: 10.1109/MCOM.2018.1700430
    [5] 陈唯实, 黄毅峰, 陈小龙, 等. 机场净空区飞鸟与非合作无人机目标识别[J]. 民航学报,2020,4(3):27-33.

    CHEN Weishi, HAUNG Yifeng, CHEN Xiaolong, et al. Identification of flying birds and non-cooperative UAV targets in airport clearing areas[J]. Journal of Civil Aviation,2020,4(3):27-33.
    [6] KITTLE D S, MARKS D L, SON H S, et al. A testbed for wide-field, high-resolution, gigapixel-class cameras[J]. Review of Scientific Instruments,2013,84(5):386-389.
    [7] 谢家阳, 王行健, 史治国, 等. 动态云台摄像机无人机检测与跟踪算法[J]. 智能系统学报,2021,16(5):858-869. doi: 10.11992/tis.202103032

    XIE Jiayang, WANG Xingjian, SHI Zhiguo, et al. Dynamic gimbal camera UAV detection and tracking algorithm[J]. Journal of Intelligent Systems,2021,16(5):858-869. doi: 10.11992/tis.202103032
    [8] 常昊. 低空飞行目标检测系统设计[D]. 西安: 西安电子科技大学, 2020.

    CHANG Hao. Design of low altitude flight target detection system[D]. Xi'an: Xi'an University of Electronic Science and Technology, 2020.
    [9] TANG J W, SHAIKH H N, SHEIKN U U, et al. FPGA-based real-time moving target detection system for unmanned aerial vehicle application[J]. International Journal of Reconfigurable Computing,2016,缺卷期号:1-16.
    [10] AMIR H R, TABERNER A J, NASH M P, et al. Suitability of recent hardware accelerators (DSPs, FPGAs, and GPUs) for computer vision and image processing algorithms[J]. Signal Processing Image Communication,2018,68:101-119. doi: 10.1016/j.image.2018.07.007
    [11] 冈萨雷斯, 伍兹. 数字图像处理[M]. 第3版. 阮秋琦, 阮宇智, 等, 译. 北京: 电子工业出版社, 2017: 254-257.

    RAFAEL C G, RICHARD E W. Digital image processing [M]. 3rd ed. RUAN Qiuqi, RUAN Yuzhi, et al, Transl. Beijing: Electronic Industry Press, 2017: 254-257.
    [12] LI B, ZAN S S, JING Q Y, et al. Detection and tracking method for maneuvering targets using improved gradient-based optical flow field[C]. 缺出版地: 2019 Chinese Control And Decision Conference (CCDC), 2019: 1421-1425.
    [13] POLMOTTAWEGEDARA S S, MUNASINGHE R, DAVARI A. Tracking moving targets[C]// Symposium on System Theory. IEEE, 2006.
    [14] LIPTON A J, FUJIYOSHI H, PATIL R S. Moving target classification and tracking from Real-time video[C]// 缺出版地: Applications of Computer Vision, 1998

    WACV '98. Proceedings. Fourth IEEE Workshop on. IEEE, 1998.
    [15] 陈科成, 苏成悦, 何雷, 等. 基于ZYNQ架构的运动物体检测系统[J]. 信息技术与信息化,2020(3):63-66. doi: 10.3969/j.issn.1672-9528.2020.03.022

    CHEN Kecheng, SU Chengyue, HE Lei, et al. ZYNQ architecture-based moving object detection system[J]. Information Technology and Informatization,2020(3):63-66. doi: 10.3969/j.issn.1672-9528.2020.03.022
    [16] 王俊龙. 基于FPGA的运动目标检测系统的设计[D]. 太原: 中北大学, 2021.

    WANG Junlong. Design of FPGA-based motion target detection system[D]. Taiyuan: North Central University, 2021.
    [17] 邢凯. 基于FPGA的多运动目标检测技术研究[D]. 昆明: 昆明理工大学, 2020.

    XING Kai. Research on FPGA-based multi-motion target detection technology[D]. Kunming: Kunming University of Technology, 2020.
    [18] 戴万. 基于FPGA的星载舰船目标检测系统设计与实现[D]. 武汉: 华中科技大学, 2018.

    DAI Wan. Design and implementation of FPGA-based target detection system for starboard ships[D]. Wuhan: Huazhong University of Science and Technology, 2018.
    [19] 张涛. 机场管制塔台通视能力评估方法研究[D]. 天津: 中国民航大学, 2017.

    ZHANG Tao. Research on the evaluation method of airport control tower visibility capability[D]. Tianjin: Civil Aviation University of China, 2017.
    [20] GOYETTE N, JODOIN P M, PORIKLI F, et al. Changedetection. net: A new change detection benchmark dataset[C]//缺出版地: Computer Vision & Pattern Recognition Workshops. IEEE, 2012.
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  • 网络出版日期:  2022-07-06

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