Identification method of 8psk signal and pi/4-dqpsk signal

Abstract

The invention discloses an identification method for an 8PSK (8 Phase Shift Keying) signal and a PI / 4-DQPSK (PI / 4-Differential Quadrature Phase Shift Keying) signal. The identification method comprises the following steps: extracting an instantaneous phase from a down-converted I / Q signal; calculating phase difference of adjacent code elements based on the instantaneous phase; calculating center normalized instantaneous phase difference based on the phase difference of the adjacent code elements; calculating a parameter based on the center normalized instantaneous phase difference; calculating absolute value standard derivation of a nonlinear component of the parameter; identifying the signal according to the absolute value standard derivation, wherein the signal is the PI / 4-DQPSK signal when the absolute value standard derivation is equal to 0 and is the 8PSK signal when the absolute value standard derivation is greater than zero. According to the technical scheme, the 8PSK signal and the PI / 4-DQPSK signal can be easily, conveniently and effectively identified.

Description

technical field [0001] The invention relates to the field of radio monitoring, in particular to a method for identifying an 8PSK signal and a PI / 4-DQPSK signal. Background technique [0002] In the field of radio monitoring, it is often necessary to identify signals such as illegal radio services and interference sources. Only when the signals are identified can they provide a basis for spectrum management. At present, the existing modulation identification methods are mainly based on extraction features. The extraction features mainly include the following: instantaneous features including amplitude, frequency and phase, statistical features and transform domain features. Among them, statistic features (such as high-order cumulants) and transform domain (such as wavelet transform) feature engineering are complicated to calculate and have poor real-time performance. At present, the most effective method for identifying features is the Digital Modulated Signal Identification...

AI Technical Summary

Problems solved by technology

Among them, statistical features (such as high-order cumulants) and transform domain (such as wavelet transform) feature engineering calculations are complex and real-time performance is poor

At present, the more effective identification method is the digital modulation signal identification algorithm (DMRAs) proposed by British scholars A.K.Nandi and Azzouz, which uses key characteristic parameters such as instantaneous envelope, phase and frequency as the characteristics of modulation identification. The algorithm calculates The speed is fast, the classification effect is obvious, and it is easier to implement in engineering, but there is no corresponding feature extraction algorithm between some signals, such as the identification between QPSK and OQPSK, the identification between 8PSK signals and PI / 4-DQPSK signals, DMRAs do not give the corresponding feature extraction parameters

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