基于频率模型和时频分析的正弦信号频率高精度估计算法

Precise frequency estimation algorithm of sinusoidal signals based on frequency model and time-frequency analysis

  • 摘要: 利用时频分析方法估计信号瞬时频率,在低信噪比条件下估计性能较差,但在时频图中,信号频率的变化趋势具有一定的规律,基本上都是围绕着信号的真实频率。基于此,给出了一种结合时频分析和信号频率模型相结合的方法,以实现信号瞬时频率的高精度估计。利用时频分析具有的良好时频分布的特点,采用最大能量方法(ME)预先估计得到信号的预估计瞬时频率(EIF);再利用瞬时频率连续性、平滑性的先验信息,建立了信号瞬时频率估计模型,并采用概率最大原理(MP)估计瞬时频率概率最大的统计变化,估计得到预估计瞬时频率的滤波起始点;最后利用卡尔曼滤波和平滑算法对预估计瞬时频率进行滤波和平滑,从而得到信号频率的精确估计。

     

    Abstract: The instantaneous frequency of signal can be estimated by time-frequency analysis, the estimation performance is inferior in the low SNR, but the variational trend of the signal frequency is well-regulated and is surrounded the true frequency. So, the estimation method of signal frequency via time-frequency analysis and frequency model is presented in the paper. Firstly, for the TF analysis can highlight the TF distribution of signals, the estimated instantaneous frequency(EIF) of signals is got by detecting the maxima energy positions of TF energy signal; secondly, using the a priori knowledge of smoothness and continuity of the IF, the model of the IF estimation is analyzed, and the trend of the IF is estimated via maxima probability principle, then the initiative position of the filter is found; finally, the EIF is filtered and smoothed through kalman filter and kalman smoother, then the precise estimation of the signal IF is achieved.

     

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