Proc. SPIE. 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018)
KEYWORDS: Signal to noise ratio, Principal component analysis, Detection and tracking algorithms, Sensors, Feature extraction, Signal processing, Target recognition, Electronic filtering, Defense technologies, Acoustics
Feature extraction based on Gammatone filterbank is more robust than that from Mel filterbank in underwater acoustic recognition. However, both conventional auditory features only represent the energy-based amplitude of the signal, and their performance decrease in low underwater SNR environments. Phase represented by instantaneous frequency (IF) may also contain some characteristics of the target. This paper proposes a novel fusion feature based on the outputs of Gammatone filters, in which an optimized algorithm of instantaneous frequency is given. Experiments employs Support Vector Machine (SVM) as the classifier and relative results indicate that significant performance gains can be obtained with instantaneous frequency information in low noise conditions.