基于FFT滑动平均极大似然法的正弦信号频率估计

FFT-Based Moving Average Maximum Likelihood Single-tone Frequency Estimation

该文基于正弦信号采样序列的FFT频谱,利用谱图上多条显著谱线与峰值谱线实部之间的关系,推导建立了一用于信号频率估计的滑动平均模型,基于此模型得出的极大似然频率估计器结合传统的Quinn方法后得到一种新的基于FFT谱滑动平均极大似然估计算法。仿真实验表明该算法精确有效,估计性能优于Rife,Quinn法,十分接近CRLB下限,计算量不大且信噪比门限要求可降至-9dB左右。

Based on the FFT of a single-tone sequence, this paper presents a novel Moving Average Maximum Likelihood （MAML） frequency estimator, which develops a Moving Average （MA） model by the real part relationship between different significant FFT coefficients firstly and a MA model-based maximum likelihood estimation technique. Simulation results show that the algorithm is effective and the proposed estimator outperforms the traditional Rife＇s and Quinn＇s estimator in both accuracy and the CRLB approximate RMSE of estimation. It is also shown that MAML has the merit of little computation effort and as lower SNR threshold as to -9dB.