A method for extracting and identifying features of radio frequency fingerprints based on bimaxima

Abstract

The invention discloses a method for extracting and identifying radio frequency fingerprint features based on bimaximum values, comprising the following steps: S1. The receiving end receives signals from a plurality of radio frequency transmitters respectively, and collects samples to obtain a sample set D; S2 Select sample data from the sample set D, extract the maximum value in the sample data, and use the selected maximum value to form sample features; S3. Process each sample data in the sample set D in turn according to step S2, Obtaining a bimaximum feature set; S4. Based on a machine learning algorithm, a classifier is trained on the basis of a bimaximum data set to identify an unknown radio frequency transceiver. The present invention utilizes the way of extracting the bimaximum values ​​to effectively reduce the extracted feature dimension, thereby reducing the computational complexity, and at the same time improving the category separability of the features.

Description

technical field [0001] The invention relates to the field of communication equipment access authentication, in particular to a method for extracting and identifying features of radio frequency fingerprints based on double maxima, which can be applied to terminal equipment access authentication. Background technique [0002] The importance of access authentication is self-evident as the first step in ensuring the secure transmission of communications. Authentication is generally carried out through a security protocol. The implementation of the authentication protocol is based on a cryptographic mechanism. If the key is leaked, the existing authentication mechanism will not be able to realize the authentication business it claims. The non-password authentication method based on radio frequency fingerprint is to confirm the terminal device according to the radio frequency fingerprint identification of the terminal device. safety performance. In particular, this method is asy...

AI Technical Summary

Problems solved by technology

Feature extraction is an important part of the radio frequency fingerprint identification process. Its purpose is to extract subtle features that can reflect the differences of different signals. However, in the existing radio frequency fingerprint feature extraction and identification schemes, the features extracted by most methods have large dimensions. Features, which select features that are more conducive to classification and discrimination for subsequent data processing, reducing data storage

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