Research on Target Polarization Recognition and Classification Based on BP Neural Network

被引:0
|
作者
Wu, Bang [1 ]
Jia, Qi [1 ]
Xu, Wei-dong [1 ]
Lv, Xu-liang [1 ]
Hu, Jiang-hua [1 ]
机构
[1] PLA Univ Sci & Technol, Coll Field Engn, Nanjing 210007, Jiangsu, Peoples R China
关键词
Polarization Detection; Stokes Parameter; BP neural network; Recognition;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Polarization detection technology has become an important means of detection technology. This paper discusses the principle and measuring method of polarization detection, typical features and the polarization characteristics, such as rock, concrete, soil, vegetation and military targets. According to the feature of polarization information, the model of target polarization recognition and classification based on BP neural network is constructed. And to validate the precision of this recognition and classification method t the experiment is organized. The results show that the scattering light polarization information as the classification basis is reliable and the model accuracy reached more than 85%, which have a good performance and can be used in many areas.
引用
收藏
页码:453 / 455
页数:3
相关论文
共 50 条
  • [41] Recognition of industrial parts based on BP neural network
    Liu, B
    Jiang, LF
    Shi, LH
    [J]. PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION SCIENCE AND TECHNOLOGY, VOL 2, 2002, : 794 - 798
  • [42] Research on recognition method of cloud precipitation particle shape based on BP neural network
    Dong, Haonan
    Jiao, Ruili
    Huang, Minsong
    [J]. 2020 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE COMMUNICATION AND NETWORK SECURITY (CSCNS2020), 2021, 336
  • [43] Study on Recognition and Classification of Blood Fluorescence Spectrum with BP Neural Network
    Gao Bin
    Zhao Peng-fei
    Lu Yu-xin
    Fan Ya
    Zhou Lin-hua
    Qian Jun
    Liu Lin-na
    Zhao Si-yan
    Kong Zhi-feng
    [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38 (10) : 3136 - 3143
  • [44] Service Classification Based on Improved BP Neural Network
    Zhu, Qiliang
    Wang, Shangguang
    Sun, Qibo
    Hsu, Ching-Hsien
    Yang, Fangchun
    [J]. JOURNAL OF INTERNET TECHNOLOGY, 2018, 19 (02): : 369 - 379
  • [45] RADAR TARGET RECOGNITION BASED ON NEURAL NETWORK
    Zhao Qun Bao Zheng Ye Wei (Institute of Electronics Engineering
    [J]. Journal of Electronics(China), 1996, (01) : 1 - 10
  • [46] A BP Neural Network Diagnosis Based on Fuzzy Classification
    Zhou Chenghua
    Ren Gongwei
    [J]. 2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31, 2008, : 5330 - +
  • [47] Target Recognition Based on Convolutional Neural Network
    Wang Liqiang
    Wang Xin
    Xi Fubiao
    Dong Jian
    [J]. LIDAR IMAGING DETECTION AND TARGET RECOGNITION 2017, 2017, 10605
  • [48] Text sentiment classification based on BP neural network
    Cheng, Nanchang
    Soong, Wenchao
    Song, Kang
    [J]. 2021 21ST ACIS INTERNATIONAL WINTER CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD-WINTER 2021), 2021, : 1 - 4
  • [49] The Automatic Classification of ECG Based on BP Neural Network
    Yu, Lanlan
    Tan, Boxue
    Meng, Tianxing
    [J]. NANOTECHNOLOGY AND COMPUTER ENGINEERING, 2010, 121-122 : 111 - 116
  • [50] Satellite target recognition algorithm based on BP neural networks
    Liu Xiankang
    Gao Meiguo
    Fu Xiongjun
    [J]. ICIEA 2007: 2ND IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-4, PROCEEDINGS, 2007, : 1775 - 1778