混沌背景中信号参数估计的新方法

怎样提取混沌背景中信号的参数具有重要意义.在重构的相空间中，叠加有其他信号的混沌信号时间序列重构的点集会偏离混沌吸引子所在光滑流形，依据这一性质并综合利用混沌背景中信号本身的特性，提出一种参数估计的新方法：最小相对奇异值(MRSV)法.该方法先建立逆滤波器，由其输出重构相空间，然后改变其参数，使输出信号在嵌入空间中作局部奇异值分解的相对奇异值最小，来实现参数估计.AR模型参数和正弦信号频率估计的仿真结果验证了该方法的有效性. 关键词： 混沌 参数估计 最小相对奇异值(MRSV) 逆滤波器

A novel parameter estimation method of signal in chaotic background

To estimate the parameters of signal in chaotic background is very important. A novel method named minimization of relative singular value(MRSV) is proposed in this paper, which is based both on the fact that points reconstructed from the mixed signal time series typically lie off the embedded image of the manifold for the dynamics underlying the chaotic time series, and also on the characteristic of the signal in chaotic background. The parameter estimation can be achieved by minimizing the relative singular value of the output of an inverse filter of the received signal in a reconstructed phase space. Several experiments of estimating the AR model parameters and sinusoidal signal frequency are carried out to confirm the effectiveness of the method.