Higher-order Statistics Characteristics Of Ship Noise Envelope

Higher-order Statistics (HOS) is the primary analysis tool in analyzing non-Gaussian signal and nonlinear signal. It has plenty of application in signal detection, feature extraction and parameter estimation. Based on the HOS, the features of ship-radiated noise are extracted and the three types of ship are classified in this paper.First, the definition and properties of HOS are introduced. We especially notice that HOS is insensitive to Gaussian process. This is the theoretical basis of signal detection and estimation.And then, the mechanism of ship-radiated noise is analyzed. With Hilbert transform, the envelop spectrum of the signals radiated from ships was obtained. The ship radiated noise is analyzed and its 4 features are extracted from the envelop spectrum. The envelope of ship noise waveform can be demodulated utilizing Hilbert transform, and the spectrum components with line rotation frequency of propeller shaft are extracted effectively by Bispectrum,1(1/2)Spectrum and 2(1/2)Spectrum analysis.A B-P neural network classifier is designed to the classification of three types of ship by using the feature vectors. The average correct recognition rate of three types ship reaches to 80%. The result show that the above techniques based on HOS are valid.In view of heavy task in the paper, it is worthy to research more in eliminating the background noise and choosing features for better underwater targets recognition and classification result in the future work.