The invention belongs to the technical field of
radio signal identification, and particularly relates to an ultrashort wave specific
signal identification method based on a
convolutional neural network. The method comprises the following steps: performing short-time
Fourier transform for a specific
signal in a sample
library, and acquiring a
signal time-
frequency spectrum, wherein the specific signal is a signal containing a
frame synchronization code in a signal transmission data frame structure; training a
convolutional neural network model with the time-
frequency spectrum; and identifying the specific signal in ultrashort wave communication through the trained
convolutional neural network model. In the method provided by the invention, firstly, visual characteristics, presented on the time-
frequency spectrum, of the specific signal are analyzed, and training is executed through the convolutional neural
network model, thus, identification of the ultrashort wave specific signal is realized, and signal
identification rate is improved; and finally, through a
simulation experiment, influence of
aliasing interference on an ultrashort wave channel is reduced effectively, ultrashort wave specific signal identification under low signal-to-
noise rate is realized, moreover, anti-interference performance can be improved through optimizing network structures and increasing the number ofnetwork
layers, so the method provided by the invention has relatively strong practical application value.