Fingerprint Feature Extraction Method, Identity Detection Method and Radiation Source Identification Correction Method

Abstract

The invention relates to a phase prediction error fingerprint feature extraction method, a user identity detection method and a radiation source identification correction method based on the feature, the correction method includes: performing parameter estimation on the received signal of each time slot in the burst data; obtaining The phase prediction error of each time slot in the burst data; the phase prediction errors of multiple time slots in the set time period are summarized to obtain the phase prediction error vector; the curve is drawn according to the error vector in ascending order, and the detection threshold is obtained. The user identity of the gap is detected; the user identity detection result is used as prior information to correct the original identification result of the radiation source to obtain the final identification result of the radiation source. The present invention proposes to use the continuity of adjacent time slots on the carrier phase as a fingerprint feature, use this feature to judge whether the user identities of adjacent time slots are the same, and use this as prior information to correct the original recognition results, and the recognition rate is obtained. It is effectively improved and has strong practical application value.

Description

technical field [0001] The invention belongs to the technical field of satellite communication security, in particular to a phase prediction error fingerprint feature extraction method, a user identity detection method and a radiation source identification and correction method based on the feature. Background technique [0002] In the satellite communication system, specific emitter identification (SEI, Specific Emitter Identification), also known as emitter fingerprint identification, is to realize the identification of the target individual by extracting the subtle features of the radio frequency signal that can reflect the individual differences of the emitter. Since the radio frequency fingerprint (RFF, Radio Frequency Fingerprinting) feature does not depend on the communication content and is difficult to forge, it has important application value in civil and military fields such as wireless network security and communication reconnaissance and countermeasures. [0003...

AI Technical Summary

Problems solved by technology

Although there are many methods for extracting RFF features, the existing methods lack targeted consideration of the characteristics of time division multiple access (TDMA, time division multiple access) signals, especially in the case of low signal-to-noise ratio or short bursts. The extraction accuracy of existing features is often low, resulting in poor recognition results

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