基于深度学习的水下目标声学识别与定位技术研究
作者:
作者简介:

岳成海(1989-),男,硕士生,主要从事模式识别与机器视觉研究。

中图分类号:

TP242

基金项目:

国家自然科学基金面上项目(42176194);国家重点研发计划资助项目(2017YFC0821204)


Research on Underwater Target Recognition and Location Technique Based on Deep Learning
Author:
  • YUE Chenghai

    YUE Chenghai

    State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016 ,China ;Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences Shenyang 110169 ,China ;Key Laboratory of Opto-Electronic Information Technology,Chinese Academy of Sciences,Shenyang 110169 ,China
    在期刊界中查找
    在百度中查找
    在本站中查找
  • WANG Xu

    WANG Xu

    State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016 ,China ;Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences Shenyang 110169 ,China ;Key Laboratory of Opto-Electronic Information Technology,Chinese Academy of Sciences,Shenyang 110169 ,China
    在期刊界中查找
    在百度中查找
    在本站中查找
  • GONG Junling

    GONG Junling

    State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016 ,China ;Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences Shenyang 110169 ,China ;Key Laboratory of Opto-Electronic Information Technology,Chinese Academy of Sciences,Shenyang 110169 ,China
    在期刊界中查找
    在百度中查找
    在本站中查找
  • ZENG Junbao

    ZENG Junbao

    State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016 ,China ;Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences Shenyang 110169 ,China ;Key Laboratory of Marine Robotics,Liaoning Province,Shenyang 110169 ,China
    在期刊界中查找
    在百度中查找
    在本站中查找
  • XU Gaopeng

    XU Gaopeng

    State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016 ,China ;Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences Shenyang 110169 ,China ;Key Laboratory of Marine Robotics,Liaoning Province,Shenyang 110169 ,China
    在期刊界中查找
    在百度中查找
    在本站中查找
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • | |
  • 文章评论
    摘要:

    为实现自主水下潜器(Autonomous Underwater Vehicle,简称 AUV)的自主目标探测识别与定位任务,以侧扫声呐数据为依据,考虑到扫描式声呐成像的特点,针对金属球类目标,基于 Darknet 框架设计了一种轻量化深度学习目标识别模型,并结合人工特征进行目标特性分析。同时对声呐图像设计了有效的图像增强方法。实验表明:上述目标识别方法在保证目标识别准确率的同时,具有较高的目标识别速率,适于低功耗嵌入式平台部署。

    Abstract:

    In order to realize autonomous target detection,recognition and positioning task of autonomous underwater vehicle(AUV),basing on the side-scan sonar data and considering the characteristics of side-scan sonar images,a lightweight deep learning target recognition model is designed in this paper based on Darknet framework for metal balls. And the characteristics of metal balls are analyzed combining with artificial characteristics. At the same time,an effective image enhancement method is designed for sonar images. Experiments show that the objects recognition method described in this paper not only ensures the accuracy of target recognition,but also provides a high processing rate,which is suitable for the low-power embedded platform.

    参考文献
    相似文献
    引证文献
引用本文

岳成海,王旭,宫俊玲,等.基于深度学习的水下目标声学识别与定位技术研究[J].数字海洋与水下攻防,2021,4(6):492-497

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 在线发布日期: 2022-01-14
文章二维码