Open AccessA Fast Instantaneous Frequency Estimation for Underwater Acoustic Target Feature Extraction
Author(s) -
Yanxin Ma,
Yifan Zhang,
Jiahua Zhu,
Ke Xu,
Yujin Cai
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2031/1/012018
Subject(s) - feature extraction , instantaneous phase , computer science , frequency domain , computation , pattern recognition (psychology) , noise (video) , speech recognition , underwater , signal (programming language) , feature (linguistics) , artificial intelligence , time–frequency analysis , signal processing , acoustics , algorithm , computer vision , digital signal processing , physics , linguistics , oceanography , philosophy , filter (signal processing) , computer hardware , image (mathematics) , programming language , geology
Traditional auditory features merely present the amplitude characteristics of target signals in frequency domain. Such features are susceptible to environmental noise, resulting in significant degradation of recognition stability. Inspired by instantaneous information applied in speech signal processing field, this paper proposed a feature extraction method using sub-based instantaneous frequency. A fast instantaneous frequency information extraction algorithm is proposed with the normalized Gammatone filterbanks. Experiments confirm that the proposed feature extraction method can effectively maintain the recognition accuracy under low SNR conditions while reduce the computation cost.