Infrared and Laser Engineering, Volume. 54, Issue 4, 20250082(2025)

Multi-type target hydroacoustic detection based on time-space two-dimensional Kalman filter and Φ-OTDR (invited)

Jinyi WU1,2, Zhaoyong WANG1,2、*, Yifan LIU1,2, Yici CHEN1,2, Boqi CHEN1,2, Feifei SONG1,2, Xuan LI1, Haoyang PI1, Qing YE1,2, Kan GAO1, Haiwen CAI1, and Ronghui QU1
Author Affiliations
  • 1Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
  • 2Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
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    Figures & Tables(13)
    Filtering direction of two-dimensional Kalman filter algorithm
    The simulation results of conventional unwrap method. (a) The unwrap results of different repetition frequency signals; (b) The unwrap results of different phase peak-to-peak value signals
    The simulation results of one-dimensional Kalman unwrap method. (a) The unwrap results of different repetition frequency signals; (b) The unwrap results of different phase peak-to-peak value signals
    The results of conventional unwrap, 1D Kalman filtering and 2D Kalman filtering algorithms for signals with a frequency of 5 kHz and a phase peak-to-peak value of (a) 3.6 rad, (b) 4.8 rad, (c) 6.2 rad, (d) 7.9 rad, (e) 9.8 rad and (f) 11.1 rad
    The experimental layout diagram
    Experimental object pictures. (a) ROV; (b) Bionic fish; (c) Divers simulation
    The results of ROV signals using conventional unwrap method compared with (a) one-dimensional Kalman unwrap method and (b) space-time two-dimensional Kalman unwrap method
    (a) Spectrogram of ROV; (b) Trajectory of ROV
    (a) PSD comparison of ROV and background noise; (b) PSD comparison of 3 times work of ROV
    (a) Trajectory of bionic fish; (b) Spectrogram of bionic fish
    Spectrogram of oxygen cylinder bubble
    • Table 1. Average computing time of 2D Kalman unwrap, 1D Kalman unwrap and conventional unwrap

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      Table 1. Average computing time of 2D Kalman unwrap, 1D Kalman unwrap and conventional unwrap

      Unwrap methodAverage computing time/s
      2D Kalman unwrap0.191819
      1D Kalman unwrap0.158749
      Conventional unwrap0.122268
    • Table 2. Summary of hydroacoustic characteristics of different targets

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      Table 2. Summary of hydroacoustic characteristics of different targets

      TargetFrequency range/HzSignal interval/s
      ROV200-1700Continuous
      Bionic fish1500-1700~0.5
      Divers simulation150-400~0.25
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    Jinyi WU, Zhaoyong WANG, Yifan LIU, Yici CHEN, Boqi CHEN, Feifei SONG, Xuan LI, Haoyang PI, Qing YE, Kan GAO, Haiwen CAI, Ronghui QU. Multi-type target hydroacoustic detection based on time-space two-dimensional Kalman filter and Φ-OTDR (invited)[J]. Infrared and Laser Engineering, 2025, 54(4): 20250082

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    Paper Information

    Category: Invited research article

    Received: Dec. 28, 2024

    Accepted: --

    Published Online: May. 16, 2025

    The Author Email: Zhaoyong WANG (wzhy0101@siom.ac.cn)

    DOI:10.3788/IRLA20250082

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