Application of the chaos, fractal and wavelet theories to the feature extraction of passive acoustic signal

Firstly, the chaos performance and the nature of nonstationary of the aerodynamic noise are discussed. Then, the distributions of the maximum Lyapunov exponent λ₁, the fractal dimension and the energy distribution indifferent wavelet scale space of the noise of the tank and helicopter are testedand analyzed statistically. Finally, these feature vectors and BP neural network are used to classify the realistic data of tank and helicopter. Results show that the classification system can achieve a statisfactory classification accuracy in different SNR.