基于时频空间奇异值分解的多分量线性调频信号的分离与增强
Multi-Component Chirp Signal Separating and Enhancing Based on SVD of Time-Frequency Space
针对加性色噪声背景下的多分量线性调频信号的分离和增强问题，本文提出了一种新的基于时频空间奇异值分解的算法，该方法对加性噪声有较好的抑制能力。同时，对于线性调频信号的最佳分数阶傅立叶变换域估计问题提出了在低信噪比下更为有效的基于信号四阶分数阶傅立叶变换中心矩的方法。仿真实验证明了本文方法的有效性。
his paper presented a new method based on singular value decomposition (SVD) of time-frequency space of observed data to separate and enhance multi-component chirp signal imbedded in additive colored noise. First, we defined a fourth-order center moment of fraction Fourier transform (Fourth-FRFT), which was useful to estimate the best FRFT domain of chirp signal when signal noise ratio was low. Then, we took advantage of Fourth-FRFT and SVD to separate and enhance contaminated chirp signal. Simulation results illustrated our method.
汪飞、孙晓颖
计算技术、计算机技术电子技术应用通信
线性调频分数阶傅立叶变换奇异值分解
chirp signalfraction Fourier transformsingular value decomposition
汪飞,孙晓颖.基于时频空间奇异值分解的多分量线性调频信号的分离与增强[EB/OL].(2009-01-19)[2025-08-05].http://www.paper.edu.cn/releasepaper/content/200901-894.点此复制
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