Envelope Phase Shift Feature Extraction of Underwater Target Echo

被引：1
|
作者：
Yong, Jintao [1 ]
Chen, Yunfei [1 ]
Zhang, Yang [1 ]
Jia, Bing [1 ]
Li, Guijuan [1 ]
机构：
[1] Sci & Technol Underwater Test & Control Lab, Dalian, Peoples R China
来源：
2019 4TH INTERNATIONAL CONFERENCE ON COMMUNICATION, IMAGE AND SIGNAL PROCESSING (CCISP 2019) | 2020年 / 1438卷
关键词：
D O I：
10.1088/1742-6596/1438/1/012004
中图分类号：
TB8 [摄影技术];
学科分类号：
0804 ;
摘要：
Aiming at the problem of target classification with different physical property parameters, the phase characteristics of echo envelope associated with different physical property parameters are studied, and the feature extraction method of the phase shift characteristics of the target echo envelope is established. The extraction method and the feature resolution performance of the phase shift characteristics of echo envelope are verified by the water-tank test of cylindrical targets with different materials and finite length. The experimental results of the underwater cylindrical target echo show that the feature of target echo envelope phase shift has significant difference with the change of target material, structure and radial scale. The phase shift feature of underwater target echo envelope has good performance for targets with different physical property parameters.
引用
收藏
页数：9
相关论文
共 50 条
  • [31] Research on technologies of underwater feature extraction and target location based on binocular vision
    Zhang Mingjun
    Li Shupeng
    Li Xuan
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 5778 - 5784
  • [32] UNDERWATER TARGET FEATURE EXTRACTION AND CLASSIFICATION BASED ON GAMMATONE FILTER AND MACHINE LEARNING
    Zhang, Wen
    Wu, Yanqun
    Wang, Dezhi
    Wang, Yongxian
    Wang, Yibo
    Zhang, Lilun
    PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR), 2018, : 42 - 47
  • [33] Tensor feature extraction of underwater passive sonar target based on auditory model
    Kang, Chunyu
    Xia, Zhijun
    Zhang, Xinhua
    Zhang, Yi
    Guo, Dexin
    Shengxue Xuebao/Acta Acustica, 2020, 45 (06): : 824 - 829
  • [34] Deep Learning Feature Extraction for Target Recognition and Classification in Underwater Sonar Images
    Zhu, Pingping
    Isaacs, Jason
    Fu, Bo
    Ferrari, Silvia
    2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2017,
  • [35] Study on the feature extraction and classification of underwater target radiated noise based on bispectrum
    Peng Yuan
    Cao Lin
    Mu Lin
    Zhang Fengzhen
    Zhang Zhaohui
    SIXTH INTERNATIONAL CONFERENCE ON ELECTRONICS AND INFORMATION ENGINEERING, 2015, 9794
  • [36] Feature Extraction of Underwater Acoustic Signal Target Using Machine Learning Technique
    Ashok, P.
    Latha, B.
    TRAITEMENT DU SIGNAL, 2024, 41 (03) : 1303 - 1314
  • [37] Feature extraction of underwater target acoustic signals based on deep manifold learning
    Zhou, Yu
    Wang, Jin
    Teng, Fei
    Pan, Bisheng
    Wang, Yourui
    Lei, Yingke
    Zhendong yu Chongji/Journal of Vibration and Shock, 2024, 43 (09): : 50 - 59
  • [38] Underwater Acoustic Target Recognition with a Residual Network and the Optimized Feature Extraction Method
    Hong, Feng
    Liu, Chengwei
    Guo, Lijuan
    Chen, Feng
    Feng, Haihong
    APPLIED SCIENCES-BASEL, 2021, 11 (04): : 1 - 12
  • [39] Tensor feature extraction of underwater passive sonar target based on auditory model
    KANG Chunyu
    XIA Zhijun
    ZHANG Xinhua
    ZHANG Yi
    GUO Dexin
    Chinese Journal of Acoustics, 2020, 39 (03) : 341 - 350
  • [40] A performance evaluation methods based on instantaneous frequency feature of underwater target echo blind separation
    Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin
    150001, China
    不详
    150001, China
    Shengxue Xuebao, 5 (655-664):
12345