Classification for underwater small targets with different materials using bio-inspired Dolphin click

Abstract

Recognition of material for underwater small targets is an extremely difficult task for the traditional CW and LFM signal. In order to distinguish different material types of underwater small targets with the same size and geometry, a series of broadband, transient-like bio-inspired dolphin sonar signals (clicks) are used as the transmitting waveform. In the joint time-frequency space, Reduced Interference Distribution (RID) is used to analyze the echoes, and then the RID-SV feature is extracted by singular value decomposition (SVD). The Support Vector Machines (SVM) are used to classify echoes. In order to verify the efficiency of the bio-inspired click signal for distinguishing materials, an anechoic pool experiment was conducted. In this experiment, three bio-inspired dolphin signals are generated by two linear frequency modulation component covering different frequency band in 40-80 kHz. These three signals are used to detect and recognize three 10 cm diameter solid spherical targets with different materials (copper, aluminum, stainless). Experimental results show that these spherical targets can be classified according to the bio-inspired dolphin click echo; Results also suggest that the classification of underwater small targets made form different materials can be improved by altering energy distribution of the bio-inspired signal in the frequency space.