A New Method of Ship Type Identification Based on Underwater Radiated Noise Signals

Abstract

Ship type identification is an important basis for ship management and monitoring. The paper proposed a new method of ship type identification by combining characteristic parameters from the energy difference between high and low frequencies and the sensitive IMF variance mean value based on the modal decomposition of the underwater radiated noise signals using the Ensemble Empirical Mode Decomposition (EEMD) method. The comparison shows that the characteristic parameters of different types of ship, underwater radiated noises are different, whereas those of the same types of ship, underwater radiated noises fall in close range. Validation experiments based on randomly selected ship underwater radiated noise samples manifest that the method is of good separability for the four types of ship underwater radiated noises in the Deepship dataset. It has a higher identification rate than other methods within the distance range of ship underwater radiated noise detection in the dataset. The accuracy of this method tends to decrease with distance in the classification experiments of the ship underwater radiated noises at different distances.

Keywords

• signals processing
• ship underwater radiated noise
• ship type identification
• ensemble empirical mode decomposition