Underwater objects classifier based on super-resolution spatial spectrum variance

Abstract

In underwater environment, the low speed target recognition has been a challenge problem. A design for underwater objects identification is suggested in this paper. The construction can be used in harbor surveillance and ocean environment inspection. Utilizing super-resolution beamforming, the distinctions between the low-speed object (such as buoy or low speed AUV) and the beacon can be observed in spatial-temporal spectrum. Corresponding to the features of power differences and spatial spectrum variance in vertical direction, the low-speed object can be separated from beacon. The data from lake experiment is dealt with and illustrate the method.