Modulation recognition method based on hsca to extract communication signal features

Abstract

The invention discloses a modulation recognition method of extracting communication signal features on the basis of HSCA (Hilbert Schmitt Component Analysis). The nature of a priori signal carrier information unused in a feature extraction process is utilized to realize modulation recognition of communication signals in a case of a low signal-to-noise ratio. The method includes the specific stepsof: 1, obtaining a normalized communication signal matrix; 2, setting parameters; 3, extracting the signal features on the basis of HSCA; 4, carrying out modulation recognition of analog signals; 5, carrying out modulation identification of amplitude shift keying signals; and 6, carrying out modulation recognition of frequency shift keying signals. According to the method, the defect that the prior art cannot consider modulation recognition of the communication signals in a non-cooperative system and the case of the low signal-to-noise ratio, and recognition accuracy is not high is overcome, HSCA is employed to extract the signal features, modulation recognition accuracy of the communication signals in the non-cooperative system and the case of the low signal-to-noise ratio is improved, and a new approach is provided for feature extraction of future communication signal modulation recognition.

Description

technical field [0001] The invention belongs to the technical field of communication, and further relates to a modulation recognition method for extracting communication signal features based on Hilbert-Schmitt Component Analysis (HSCA) in the technical field of communication signal processing. The invention can be used to realize modulation identification of analog modulation signal and modulation identification of digital modulation signal in the non-cooperative communication system under the condition of low signal-to-noise ratio. Background technique [0002] Commonly used analog modulation signals are: amplitude modulation signal AM (Amplitude Modulation), frequency modulation signal FM (Frequency Modulation), and phase modulation signal PM (Phase Modulation). Commonly used digital modulation signals are: multiple amplitude shift keying MASK (Multiple Amplitude Shift Keying) and multiple frequency shift keying MFSK (Multiple Frequency Shift Keying). In the existing tec...

AI Technical Summary

Problems solved by technology

Although this method has a certain inhibitory effect on noise, the disadvantage of this method is that the extraction of high-order cumulant features requires a priori carrier frequency information of the signal or needs to accurately estimate the carrier frequency of the signal. In this scenario, the modulation method of the signal cannot be correctly identified

The disadvantage of this method is that the instantaneous characteristics are greatly affected by channel noise, and the modulation mode of the signal cannot be correctly identified in a low signal-to-noise ratio scenario.

[0005] To sum up, for the modulation recognition method of communication signals, the existing feature extraction methods do not comprehensively consider the unknown prior information of the signal and the situation of low SNR, and the extracted signal features cannot be used in non-cooperative conditions with low SNR. Realize the modulation recognition of communication signals in communication scenarios, and use existing methods for modulation recognition, but the recognition accuracy is not high

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