Feature extraction and acoustic signal recognition using principal components analysis

This paper proposes an algorithm of feature extraction from acoustic signals based on principal component analysis (PCA). Features of four types of acoustic signals of battlefield target are extracted and low-dimcnsion feature vectors obtained with this technique. K-nearest neighbor classifier and BP neural network classifier are designed for the acoustic target classification. Satisfactory experimental results have been obtained with classification accuracy reaching as high as 86%.