Signal transmitter individual recognition method based on bispectrum analysis and convolutional neural network

Abstract

The invention provides a transmitter individual recognition method based on combination of bispectrum analysis and a deep convolutional neural network. In order to cope with the increasingly complicated electromagnetic environment, intercepted radio signals need to be classified and analyzed, and different transmitters further need to be recognized. A radio signal transmitter individual recognition method adopted at present is poor in effect under the low signal-to-noise ratio condition. The transmitter individual recognition method based on combination of bispectrum analysis and the deep convolutional neural network comprises the main steps that first, signals transmitted by different transmitter individuals are analyzed through a direct bispectrum method, and thus a bispectrum feature matrix is obtained and converted into two-dimensional feature images; second, the two-dimensional feature images are classified through the convolutional neural network; and third, a classifying resultis output, and the different transmitter individuals are recognized. The transmitter individual recognition method can be applied to the fields of individual recognition of communication transmittingequipment, recognition of the various radiation source transmitters in electronic countermeasure and the like.

Description

technical field [0001] The present invention relates to a technology in the field of electronic countermeasures, in particular to a method for identifying individual signal transmitters based on bispectral analysis and convolutional neural network. Background technique [0002] Special Emitter Identification (SEI) originated from military intelligence and is used to identify and track specific transmitters, that is, to extract the radio frequency and information fingerprints of a single radiation source (possibly of the same type) and associate it with an individual carrier, The process of identifying individual radiation sources and their platforms. SEI technology achieves the purpose of reducing recognition ambiguity and improving reliability by analyzing the implicit and inherent individual characteristics in the transmitter signal, and has repeatability. However, SEI techniques for radar signal identification generally rely on high signal-to-noise ratios and good channe...

AI Technical Summary

Problems solved by technology

[0008] The problem to be solved by the present invention is that in the existing radio transmitter individual identification method, the signal fingerprint feature extraction process is complicated, a large number of calculations are required, and the identification effect is poor under low signal-to-noise ratio conditions, that is, it cannot Effective identification of individual radio transmitters

Images