Carrier frequency estimation method based on cyclic correlation entropy spectrum of compressive sensing reconstruction

Abstract

The invention belongs to the technical field of cyclic stationary signal processing and compressive sensing, and provides an amplitude modulation signal carrier frequency estimation method through cyclic correlation entropy spectrum projection after compressive sensing reconstruction. According to the method, the cyclic correlation entropy spectrum of a signal to be estimated is calculated firstly; then sampling and compression are performed on the cyclic correlation entropy spectrum through a compressive sensing method; then reconstruction of the cyclic correlation entropy spectrum is performed on the compressed data; and finally the corresponding carrier frequency of the signal is estimated through the peak of the reconstructed cyclic correlation entropy spectrum projection according to the modulation mode and the relation between the carrier frequency and the cyclic frequency. The experiment proves that the algorithm has great performance and can perform carrier frequency estimation of the signal under the condition of coexistence of non-Gaussian noise and the interference of the same frequency band and has the advantages of being low in data volume and convenient for storage and transmission.

Description

technical field [0001] The invention belongs to the technical field of cyclostationary signal processing and compressed sensing, and relates to a modulation signal carrier frequency estimation method, in particular to a method for estimating the amplitude modulation signal carrier frequency by using the reconstructed circular correlation entropy spectrum projection of compressed sensing. Background technique [0002] Traditional carrier frequency estimation methods are mainly based on the frequency spectrum or power spectrum of stationary signals, but when there is co-band interference, such methods cannot accurately realize the function of carrier frequency estimation. In order to solve this problem, researchers have proposed a carrier frequency estimation method based on cyclic correlation spectrum, which partially solves the problem of carrier frequency estimation under the same-band interference condition, but this type of method also has defects, that is, it relies heavi...

AI Technical Summary

Problems solved by technology

[0002] Traditional carrier frequency estimation methods are mainly based on the frequency spectrum or power spectrum of stationary signals, but when there is co-band interference, such methods cannot accurately realize the function of carrier frequency estimation

In order to solve this problem, researchers have proposed a carrier frequency estimation method based on cyclic correlation spectrum, which partially solves the problem of carrier frequency estimation under the same-band interference condition, but this type of method also has defects, that is, it relies heavily on Gaussian noise Assuming that the noise model does not obey the Gaussian distribution, the performance of such methods will be seriously degraded

Afterwards, aiming at the problem of carrier frequency estimation under the coexistence of impulse noise and same-band interference, researchers proposed a method based on cyclic correlation entropy spectrum. According to the characteristics of cyclic correlation entropy spectrum, when the carrier frequency is continuously , the amount of data in the cyclic correlation entropy spectrum will also continue to increase, resulting in larger storage and transmission costs, making it difficult for this type of method to be practically applied in this case

Images