α稳定分布下基于SSCA算法的低阶循环谱算法

Realization of a low order SSCA method under α stable distribution

在α稳定分布下结合共变理论、循环平稳理论和分数低阶矩(FLOM)等理论,提出基于SSCA的低阶循环谱算法,分析了该算法中存在的循环泄露,并对调幅信号做实验仿真。结果表明在α稳定分布下二阶循环平稳信号的低阶循环谱密度和在高斯模型下的循环谱结构是一致的,但基于α稳定分布假定所设计的信号处理算法对信号噪声特性不确定情况具有较好的韧性和抗脉冲噪声性能。最后利用低阶循环谱提取了调制信号的特征参数,为复杂背景下的调制识别或者盲分离提供新的途径。

A new method combining covariation, cyclostationarity and FLOM for calculating low order spectrum was proposed based on SSCA. Simulation were made for amplitude modulation signals and the result under stable distribution showed that the spectrum instruction of two order cyclostationary signals was the same as under the Gauss model. However, the methods constructed under the stable distribution had better anti-noise performance than under the Gauss model. The characteristic parameters based on modulated signals＇ low order cycle-spectrum were extracted and thus a new way was given for modulation recognition and blind separation in a complex environment.