基于广义柯西分布的最大后验准则频谱估计方法

New Method for Spectrum Estimation Based on Generalized Cauchy Distribution and MAP

经典的频谱估计方法和现代的频谱估计方法在低信噪比及小数据量的情况下,谱估计的分辨率和方差性能不能满足实际应用需要。因此,提出一种高分辨率、高精度DFT变换的新方法,此方法特别适用于线性频谱的估计。该方法基于最大后验概率准则,建立广义柯西-高斯分布模型,克服了短数据情况下的DFT变换分辨率低的缺点,具有收敛快、频率分辨率高、频率精度高的优点。计算机仿真结果证实了新方法的有效性。

In the low SNR and small amount of data,the resolution and variance performance of spectral estimation can not meet the actual requirement by using classical or modern spectrum estimation methods.Therefore,a new high-resolution and high-precision method of DFT transform is proposed.It is suitable for estimation of linear spectra.Based on maximum a posteriori probability criterion,a generalized Cauchy-Gaussian distribution model to overcome the low resolution of DFT in the case of short data is established.The proposed method has advantages of fast convergence,high efficiency and high accuracy.The results of computer simulation show that the novel method is effective.