Principal Component Analysis on Lofar Spectrum Features of Underwater Target Signals

A method for processing the features of underwater target signal based on Lofar spectrum feature extraction and principal component analysis is discussed. Features of Lofar spectrum from sonar signals are extracted and analyzed. Major theories and solutions about PCA are introduced and signals of ship-rediated noise are processed based on it. Feature dimensions of Lofar spectrum are successfully reduced and a result for the feature expression is obtained. The data are also applied to fuzzy integrated neural network classifier and it is successful than the result without processing of PCA.