Fingerprint feature extraction method, identity detection method and emitter identification and correction method

Abstract

The invention relates to a phase prediction error fingerprint feature extraction method and an identity detection method and an emitter identification and correction method based on the feature. The correction method includes the following steps: estimating the parameters of received signals in each time slot of burst data; acquiring the phase prediction error of each time slot in the burst data;aggregating the phase prediction error of multiple time slots in a set time period to obtain phase prediction error vectors; drawing a curve in ascending order of the error vectors, acquiring a detection threshold, and detecting the user identities of adjacent time slots; and correcting the original identification result of an emitter by taking the user identity detection result as priori information to obtain a final identification result of the emitter. The continuity of adjacent time slots on a carrier phase is proposed as a fingerprint feature, whether the user identities of adjacent timeslots are the same or not is judged based on the feature, and the original identification result is corrected by taking the user identity detection result as priori information. The identification rate is improved. The methods have high 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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