改进的经验模态分解盲信噪比估计方法

A Modified Blind SNR Estimator Based on Empirical Mode Decomposition

  • 摘要: 针对经验模态分解信噪比估计方法运算量大、精度低的问题,本文结合概率论提出了改进的算法。利用离散傅里叶变换分析了固有模态函数的功率谱分布情况,确定了3次分解的有效性,简化了运算过程。基于统计数据给出了分量功率谱密度分布关于特征参数的正态分布近似表达式,并分析了分解过程中存在的能量溢出现象,由此给出了由特征参数估计信噪比的方法。针对不同的样本长度和信号调制方式测试了新算法的性能,结果表明新方法的性能优于原始方法,信噪比0dB时新方法的估计误差不高于0.5dB。

     

    Abstract: Given of the weakness of SNR estimator based on Empirical Mode Decomposition,as large computation and low accuracy, a new algorithm combined with the probability theory was proposed.Analyzed the power spectrum distribution of Intrinsic Mode Functions (IMF) in the way of discrete fourier transformation, and determined the effectiveness of decomposition three times,simplified operating process. Proposed the normal distribution approximate expression of the power spectral density of components about the characteristic parameters based on statistical data, and analyzed the leakage of energy in the decomposition process,then gave the signal to noise ratio estimate method of characteristic parameters.For different sample length and data size,simulation results show that the new algorithm has a better performance in lower SNR environment,and the normalized mean square error is less than 0.5dB when SNR is 0dB.

     

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