Weak Signal Detection for UUV Based on Distributed Fiber-Optic Hydrophone

In view of the current situation that it is difficult to detect the weak signals of underwater unmanned underwater vehicle (UUV) targets in a low signal-to-noise ratio environment, based on the linear array of the ultra-fine cable diameter hydrophone with distributed optical fiber sensing, the TOC-ICEEMDAN algorithm is proposed to achieve signal noise reduction and extraction for wideband weak UUV sound sources. The tornado meta-inspired optimization algorithm is introduced to optimize the key parameters of the improved adaptive noise empirical mode decomposition algorithm. After processing multiple sets of experimental data and integrating the noise reduction indicators, the feasibility and robustness of TOC-ICEEMDAN in different situations are verified. The results show that the energy error of the proposed TOC-ICEEMDAN algorithm is 69.044 3, the average correlation coefficient is 0.341 3, and the signal-to-noise ratio is 7.718 7 dB. Compared with the traditional EEMD and ICEEMDAN algorithms, it has been greatly improved and has important application prospects in distributed optical fiber detection of weak signals underwater in UUV.