HIDR: A Hierarchical Independent Detection and Recognition strategy for underwater acoustic multi-target recognition

Abstract

This paper proposed HIDR (Hierarchical Independent Detection and Recognition), a novel strategy for underwater acoustic multi-target recognition. HIDR adopts a hierarchical architecture instead of the single-step traditional target recognition task, which is a relatively challenging task especially for the multi-target recognition. HIDR would firstly distinguish target signals from non-target signals as a detection stage, then pinpoint the specific target from all possible types of target signals as a recognition stage. This hierarchical architecture cannot only sharply reduce the difficulty of feature extraction, but also benefit for the higher recognition accuracy. A universal feature extraction strategy is utilized to extract two independent feature sets for the two stages respectively, which include auditory parameters especially adaptive to detection/recognition stages, as well as other common time/frequency domain features. Experiments with real sea trial data are conducted to compare HIDR with existing high-quality multi-target recognition schemes. Experimental results show that the proposed strategy can reach up to 88.71% of recognition accuracy in four-class recognition task, which is more than 5.25% higher than that of mainstream methods.