CAJ | 학술논문

针对传统数字调制识别方法在非高斯Alpha稳定分布噪声下识别性能差的问题,该文提出一种基于广义分数阶傅里叶变换和分数低阶Wigner-Ville分布的数字调制识别新方法.该方法提取广义分数阶傅里叶变换的零中心归一化瞬时幅度谱密度的最大值和分数低阶Wigner-Ville分布幅度的最大值作为识别特征参数,并采用判决树分类器,实现了非高斯噪声下数字调制信号识别.仿真结果表明,在非高斯Alpha稳定分布噪声下,该识别方法不仅性能明显优于传统方法并且具有较高的识别率和良好的稳健性.
침대전통수자조제식별방법재비고사Alpha은정분포조성하식별성능차적문제,해문제출일충기우엄의분수계부리협변환화분수저계Wigner-Ville분포적수자조제식별신방법.해방법제취엄의분수계부리협변환적령중심귀일화순시폭도보밀도적최대치화분수저계Wigner-Ville분포폭도적최대치작위식별특정삼수,병채용판결수분류기,실현료비고사조성하수자조제신호식별.방진결과표명,재비고사Alpha은정분포조성하,해식별방법불부성능명현우우전통방법병차구유교고적식별솔화량호적은건성.
In an Alpha stable distribution noise environment, the traditional methods of digital modulation signals recognition have the problems of poor performance. A novel recognition method based on generalized fractional Fourier transform and fractional lower Wigner-Ville distribution is proposed to solve this problem. This method extracts the recognition characteristic parameters which are maximum of normalize and center instantaneous amplitude spectral density based on generalized fractional Fourier transform and maximum of fractional lower Wigner-Ville distribution amplitude. And then the method uses decision tree as a classifier to achieve digital modulation signals recognition. Simulation results show that the proposed method not only has better performance than the traditional recognition methods but also has higher recognition rate and good robustness in an Alpha stable distribution noise environment.