一种新的平行多分量LFM信号的参数估计方法

New Parameter Estimation Method for Parallel Multi-component LFM Signals

基于Hilbert-Huang变换(HHT)能分解出信号的任何频率成份和线性调频(LFM)信号的瞬时频率是关于时间的直线的特性,对频率相近的平行多分量LFM信号进行HHT变换,再利用滤波和改进的最小二乘直线拟合,最后得到各分量较为准确的瞬时参数估计。该方法不需要改变HHT算法本身,而是利用滤波方法和进一步的最小二乘直线拟合抑制了HHT固有的边界效应对瞬时参数估计的影响,提高了频率提取的准确性,而且更容易实现。仿真结果表明该方法能成功地解决小波脊方法所不能解决的频率相距很近的平行多分量LFM信号的频率分离和参数估计问题。

The Hilbert-Huang transformation （HI-IT） can decompose signals as the sum of all their frequency components, and the instantaneous frequency of each component involved in multi-component linear frequency modulation （LFM） signals is a line with respect to the time variation. According to that, very close parallel multi-component LFM （VCPMCLFM） signals were firstly decomposed based on HHT, then instantaneous frequency lines were filtered and new instantaneous frequency lines were fitted with improved Least Squares linear fitting Method（LSLFM）, lastly rather accurate instantaneous parameter estimations for VCPMCLFM signals were obtained. The filtering method combined with the improved LSLF is adopted rather than changing the HHT algorithm to reduce the end effect inherent in HHT, leading to much more precise parameter estimation values and being implemented more easily. Simulation results show this proposed parameter estimation method can identify every component in VCPMCLFMsignals, but wavelet ridge method can＇t do that.