Method for noise abatement of LFM underwater sound multi-path signals

Abstract

The invention belongs to the field of signal processing, and particularly relates to a method for noise abatement of LFM underwater sound multi-path signals. The method includes the steps that an optimal transformation order popt on which optimal fractional Fourier transformation is conducted is acquired according to deterministic signal parameters; band-pass filtering preprocessing is conducted on the LFM multi-path signals, and out-of-band noise is abated; Hilbert transformation is conducted on band-pass filtering output signals, and then analytic signals are acquired; popt and fractional Fourier transformation is conducted on the analytic signals; frequency spectrum shielding and isolating processing is conducted on a fractional Fourier domain, and in-band noise is abated; -popt and fractional Fourier inverse transformation is conducted, and then high-signal-to-noise-ratio multi-path signals with the abated noise are acquired. The method is mainly achieved through the FFT algorithm, the calculated amount is small, and project real-time implementation can be achieved. Signal processing is not disturbed by cross terms due to FrFT linear transformation characteristics, so that the method is especially suitable for processing the multi-path or multi-component LFM signals.

Description

technical field [0001] The invention belongs to the field of signal processing, in particular to a noise suppression method for LFM underwater acoustic multi-channel signals. Background technique [0002] Noise suppression technology has always been an important research topic in the field of signal processing. Many noise suppression techniques have been proposed, such as adaptive filtering, time-domain averaging, noise suppression techniques based on wavelet analysis or neural network, etc. These noise suppression techniques have different performances and are suitable for different application requirements. [0003] The linear frequency modulation (LFM) signal is the basis of a large class of artificial signals. As a mature non-stationary signal, it has been widely used in the field of underwater acoustics, such as submarine terrain detection, submarine bottom classification, submarine shallow formation detection, underwater acoustics, etc. Channel detection, underwater s...

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Problems solved by technology

[0004] LFM noise suppression technology can be realized by filtering method, but the in-band noise cannot be effectively suppressed only by filtering technology; because LFM signal is a typical time-varying signal, it is not suitable for the Wiener filter with fixed parameters to process it ; Although the Kalman filter has time-varying parameters and is suitable for the processing of non-stationary random signals, the statistical properties of the signal and noise must be known to obtain the optimal filtering results, and the prior knowledge of these statistical properties is usually not available in practical applications. Therefore, the optimal filtering process cannot be realized; although the adaptive filter can automatically adjust the filtering parameters at the current moment to adapt to the unknown or non-stationary statistical characteristics of the signal and noise to achieve optimal filtering, but the adaptive filter exists The characteristic of asymptotic convergence, when the amount of detection data is small, the error of the initial part of the signal waveform enhanced by adaptive filtering is very significant

Many defects in existing noise suppression methods make it unsuitable for noise suppression processing of LFM underwater acoustic multi-channel signals

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