Underwater acoustic signal noise reduction method based on generative adversarial network

Abstract

The invention provides an underwater acoustic signal noise reduction method based on a generative adversarial network. The method comprises a training stage and a testing stage. The training stage comprises the following steps: inputting a noisy signal training set into a generator to obtain a generator generation signal; splicing the generator generation signal and a target signal without noise with a noisy signal respectively, and then inputting the signals into a decision device in sequence; allowing the decision device to take the noisy signal as condition information and performs true andfalse discrimination on another input signal which is input at the same time; and calculating an error between a judgment result and a real label, then updating and optimizing network parameters of the generative adversarial network by utilizing a back propagation algorithm, and obtaining a trained generator model; the testing stage comprises the following steps: inputting a to-be-tested underwater acoustic signal into the trained generator model, and taking the output of the trained generator model as a denoised underwater acoustic signal. The method is suitable for various types of signals,and has a good noise reduction effect on common underwater acoustic communication signals such as MFSK, MPSK, OFDM, LFM and DSSS.

Description

technical field [0001] The present invention relates to the technical field of signal noise reduction, in particular to an underwater acoustic signal based on generative confrontation network. [0002] Noise reduction method. Background technique [0003] Passive detection of underwater acoustic signals is an important research content in the field of underwater acoustic signal processing, and plays an important role in civil applications such as scientific investigation and maritime rescue, as well as military applications such as underwater target monitoring. However, due to the sound absorption of seawater and the complexity and changeability of marine environmental noise, the passive detection ability of underwater acoustic signals is significantly reduced under the conditions of long-distance and fluctuating marine environmental noise. The core of solving this problem is to reduce the noise of the received signal. Researching a noise reduction method that can not only ...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems that the existing noise reduction method based on signal processing has limited noise reduction ability for low signal-to-noise ratio received signals, insufficient adaptability to complex marine environment, and strong dependence on domain knowledge and human experience, the present invention provides a A Noise Reduction Method for Underwater Acoustic Signals Based on Generative Adversarial Networks

Images