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)
Fig. 1. Filtering direction of two-dimensional Kalman filter algorithm
Fig. 2. 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
Fig. 3. 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
Fig. 4. 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
Fig. 6. Experimental object pictures. (a) ROV; (b) Bionic fish; (c) Divers simulation
Fig. 7. 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
Fig. 9. (a) PSD comparison of ROV and background noise; (b) PSD comparison of 3 times work of ROV
Fig. 10. (a) Trajectory of bionic fish; (b) Spectrogram of bionic fish
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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
Category: Invited research article
Received: Dec. 28, 2024
Accepted: --
Published Online: May. 16, 2025
The Author Email: Zhaoyong WANG (wzhy0101@siom.ac.cn)