Intermediate frequency sampling sequence processing method for radiation source fingerprint feature recognition

Abstract

The invention discloses an intermediate frequency sampling sequence processing method for radiation source fingerprint feature recognition, and the method comprises the steps: carrying out the preprocessing of intermediate frequency sampling data, and obtaining a training set and a test set; establishing a seven-layer neural network, training the seven-layer neural network by adopting the trainingset, and testing the seven-layer neural network by adopting the test set to obtain a trained neural network; inputting the obtained data into a trained neural network to obtain fingerprint features;according to the invention, the problems of low efficiency and low mobility in the existing manual signal feature extraction and the problems of large data processing amount and difficulty in accuratefingerprint feature extraction in the end-to-end deep learning are solved.

Description

technical field [0001] The invention belongs to the field of communication, and in particular relates to an intermediate frequency sampling sequence processing method used for fingerprint feature identification of radiation sources. Background technique [0002] Non-cooperative communication radiation source signal identification refers to the identification of the type and carrier of communication radiation source by analyzing the collected radiation source electromagnetic signal characteristics without prior information. The research has a wide range of applications in both civilian and military applications. In the civilian field, the detection of equipment failures and the security checks of communication networks are generally carried out by manpower combined with special equipment, which requires fast and efficient automatic identification methods. In the military field, the need for radiation source identification is even more urgent, such as electronic warfare needs...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides an intermediate frequency sampling sequence processing method for radiation source fingerprint feature identification, which solves the problems of low efficiency and poor portability in the existing manual extraction of signal features, as well as terminal End-to-end deep learning has a large amount of data processing and it is not easy to accurately extract fingerprint features

Images