An auditory periphery model for underwater target narrow-band noise recognition

In order to solve the problem of recognition rate decreasing when apply the auditory periphery feature to identify the underwater target with practical application background, a Gammatone filter bank adjustment method is proposed. The narrow-band noise feature obtained may improve the recognition result significantly. Firstly, the reason of recognition result decreasing is analyzed, which is due to the mechanism of multichannel data acquisition in acoustic engineering. The decrease of sampling rate may cause the narrow down of signal frequency range, which leads to time- frequency feature distortion. Then, the Gammatone filter bank is implemented to simulate the frequency decomposition characteristics of human ear basement membrane. Since the class information of the underwater target noise signal is mostly contained in the low frequency part, the auditory feature of the conventional model is interpolated and the channel number of the filter bank and the central frequency of each frequency band are adjusted accordingly to obtain a 27-dimensional feature vector of the narrow-band target signal. The adjusted model may reflect the target's time-frequency feature more precisely. Finally, the performance of the auditory feature is tested by Neural Network classifier. The experiment result shows that the modified auditory model is more effective than the conventional ones. The majorinformation contained in broadband signals is reserved and the classification ability for real targets is further enhanced. The recognition result has increased from 82.59% to 88.80%. The proposed Gammatone filter bank adjustment method is based on effective frequency band of the data by practical application platforms. The multichannel data from the array element is used for data analyzing and the problem of recognition result decreasing due to narrow-band feature distortion is solved. The modified auditory feature may effectively improve the recognition rate for underwater target radiated noise signals. This article has a certain reference value for people doing studies and time-frequency feature analysis for acoustic data acquired by multiple active/passive sonar target recognition channels with limited frequency band.