| The method for extraction of mine characteristics based in fractional Fourier transform is studied in the dissertation. The characteristics- extraction is belonged to the category of signal processing while the thereunder of characteristics-extraction is about fluctuation of underwater acoustic. The method of signal processing—fractional Fourier transform is combined with the model of underwater target highlight to study the method of remote mine detection after having known the target characteristic.As the generalization of the Fourier transform, the fractional Fourier transform (FRFT) performs a rotation of signal in the continuous time-frequency plane to any angle. As we know, a LFM signal with proper chirp rate have the best energy concentration on the corresponding fractional domain, with this characteristics, LFM signal can be detected and estimated. So the method is putted into extracting of mine characteristics to process the target echo whose transmitted signal is LFM signal.Firstly, the detection of LFM signal in the back ground of gauss noise and reverberation using FRFT has been researched, and the method has the capability of anti-noise and reverberation. Then, in the dissertation , the simulated echo signal is processed with FRFT based in the model of underwater target highlight, and the clear elastic highlights and geometric highlights are picked up. It is proved that FRFT is an effective method to solve the problem of extraction of mine characteristics theoretically. In the end, The data of two experiments are processed. The true target, false target and reverberation are recognized through extracting the characteristics of FRFT energy peak of target echoes, and a quite ideal recognition effect is received using the feedforward BP network.
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