Radio signal identification method based on end-to-end convolutional neural network

Abstract

The present invention relates to a radio signal identification method based on an end-to-end convolutional neural network. The method is characterized in that: an original I / Q sampling data of an observation window is subjected to execution of preprocessing and identification through a convolutional neural network in order. The preprocessing step is that: the original I / Q sampling data of the observation window is taken as input, and a frequency spectrum waterfall plot is output after discrete Fourier transform and data format alignment processing; the step of identification through the convolutional neural network is that: the frequency spectrum waterfall plot obtained by preprocessing is taken as input, and a one-dimensional boolean vector configured to show whether all the signals to beidentified are existed or not is output after the input passes through a CNN feature extraction layer, an MLP feature mapping layer and a BR multi-tag classification layer. Compared with the mode offeature extraction and classification identification, the radio signal identification method employs the end-to-end technical solution thinking to avoid complex and low-efficient feature engineering,improve the signal identification accuracy, robustness and intelligence level, and has important meaning of radio monitoring of important areas and important activity scenes.

Description

technical field [0001] The invention belongs to the technical field of radio monitoring, and relates to a radio signal recognition method based on an end-to-end convolutional neural network (CNN), which is used to solve the problem of too complicated feature extraction faced in traditional radio signal recognition, and improve The ability and intelligence level of radio signal recognition. Background technique [0002] In recent years, with the development of wireless communication technology, especially the rise of the Internet of Things, radio waves have become an important carrier for connecting all things. However, the openness of radio waves makes it vulnerable to interference and illegal use, leading to serious problems such as interruption of normal communication systems and dissemination of false reactionary speeches. Therefore, radio security has become an important part of national security. Strengthening radio monitoring and management, especially radio supervisi...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is: aiming at the deficiencies of the prior art, a radio signal recognition method based on an end-to-end convolutional neural network is proposed, which deeply integrates artificial intelligence and radio signal processing technology, and solves the problems faced in traditional radio signal recognition Artificial feature extraction is too complicated to improve the recognition ability and intelligence level of radio signals

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