时频分析的卡尔曼滤波匹配解调变换法

Matching Demodulation Transform with a Kalman Filter for Time-Frequency Analyses

本文为多分量时频分析,提出了一种卡尔曼滤波的匹配解调变换的分析方法,该方法对信号的局部频率特性进行建模,以模型参数作为状态变量、以时频脊线为观测变量,分别建立起时频分析的状态方程和观测方程,据这些方程并利用卡尔曼滤波就可获得信号的瞬时频率,最后再对信号进行解调变换,就得到了能量高度集中的时频分布.在不同信噪比的情况下,仿真测试表明:本文方法优于现有文献报道方法.

This paper introduces a multi-component time-frequency analysis method,which conducts matching demodulation transform with a Kalman filter.This method builds the model on the local frequency properties of the signal,with model parameters seen as the state variables and the TF ridges treated as the observations.With the state and observation equation established,Kalman filter can be used to estimate the frequency of the signal.Finally,demodulation transform is used to generate a higher energy concentrated time-frequency distribution.The simulation results show our method has a better performance than existing methods under various SNR circumstances.