Underwater Target Identification Based on Dolphin Auditory System Model

Extracting feature information from the active sonar echo of target is an effective method to realize underwater target classification and identification. The excellent performance of animal sonar in underwater target identification provides a solution for artificial sonar. In this study, the click signal of bottlenose dolphin is used as the transmitting signal of active sonar. The echo characteristics of the target are extracted by wavelet transform and model of dolphin auditory system, and are classified as the input of support vector machine. In addition, this paper proposes an idea that the time spectrum obtained by the model based on dolphin auditory system is used as the input of convolution neural network to classify and identify the target. The results show that compared with that of the wavelet transform method, the feature extraction method based on the computer model of dolphin auditory system is better for target classification and identification. Combining with convolution neural network, using dolphin click signal and model of dolphin auditory system can obtain better results in underwater target identification.