A New Nonlinear Filtering Algorithm for Colored Background Self-Noise Suppressing of Symbol Rate Estimation
Liang Jin · Dianzi xuebao · 2007
According to the theory of cyclostationary,symbol rate of some digital modulated signals,whose symbol rate gives out basic cyclic frequency,can be retrieved by estimating cyclic frequencies of signal's nonlinear transform such as cyclic autocorrelation.Nonlinear transform of signal will generate symbol-rate sinusoidal wave and its harmonics as well as continuous colored background self-noise,which distribute mainly within low frequency band and can disturb the identification of spectral lines especially when available data is not enough.This paper delves into the frequency characteristic of nonlinear transform and proposes a novel nonlinear filtering algorithm,which can be utilized to suppress continuous colored background self-noise,based on an obvious fact that symbolrate spectral line will stand out within its nearby frequency domain,a key advantage that will never belong to continuous self-noise.All-sided Monte Carlo simulations have been carried out to justify this algorithm.