摘要
根据循环平稳有关理论,通信信号的非线性变换频谱中存在体现各阶循环平稳性的离散谱线,谱线位置对应着信号载波频率和符号速率的线性组合,提取这些谱线可以完成信号的基本参数估计。然而非线性变换不仅能产生对应于信号载波频率和符号速率等参数的正弦分量,而且还会形成不利于谱线提取的背景色噪声,当信号信噪比低、数据量小时,色噪声对谱线提取的影响尤为突出。针对这一问题;本文深入研究了信号非线性变换谱特征,结合数学形态学基本理论,提出了一种基于离散灰度形态滤波的方法来抑制背景色噪声。利用开运算估计背景色噪声,运用顶帽变换进行白化处理,通过闭运算填平杂散负脉冲,增强谱线相对强度,最后设置检测门限,提取离散谱线,完成信号相应参数的估计。详尽的Monte Carlo仿真给出了谱线检测性能与信号脉冲成型系数、信噪比和数据量之间的关系。结果表明算法有效抑制了背景色噪声,在信噪比低、脉冲成型系数小、数据量少的情况下提高了谱线检测性能,从而证实了该算法的有效性。
According to the theory of cyclostationary,some discrete spectral lines,located in the linear combination of signals＇ carrier frequencies and symbol rates,are present in the nonlinear transform of signals to reflect cyclostationarity of communication signals. So,the basic parameters can be estimated by extracting the spectral lines of nonlinear transform,but it will not only generate sinusoidal component of signal parameters,but colored-background noise will be formed as well.This phenomenon is harmful for the identification of spectral lines especially when the signal SNR（Signal-to-Noise Ratio） is low and available sampling data is not enough.Aiming at this problem,our paper delves into the frequency characteristic of nonlinear transform,employs the basic theory of mathematic morphology,and proposes a novel algorithm based on the discrete gray-scale morphologic filtering to suppress the noise.Firstly,opening operation is exploited to estimate the colored-background noise in the spectrum of signal nonlinear transform.Then top-hat operation is carried out to accomplish the whiten treatment,after filling up the miscellaneous negative pulse via closing operation,the relative amplitude of spectral lines are enhanced.Finally,setup detection threshold and locate the discrete spectral lines to accomplish the parameter estimation of signals.Take the estimation of QPSK symbol rate for example,all-sided Monte Carlo simulations are employed to show the relationship between detective performance and signals＇ pulse shape coefficient,SNR,symbols.All the simulations take another method into account as a contrast.The results indicate that the novel algorithm suppresses colored-background noise effectively and improve the lines detection capability in the case of low SNR,small pulse shape coefficient and signal symbols.Consequently,the efficiency of the proposed algorithm is confirmed.At last,in order to take full advantage of the former spectral data,a smoothing filter operation is used to improve the detective performance in the situation of low signal SNR.
出处
《信号处理》
CSCD
北大核心
2010年第11期1652-1656,共5页
Journal of Signal Processing
关键词
非线性变换
形态学
循环平稳
背景色噪声
nonlinear transform
morphology
cyclostationary
colored-background noise
