外场条件下信噪比估计算法应用研究

Research into The Application of SNR Estimation Algorithms under Out-field Condition

首先介绍了几种典型的信噪比估计算法,接着详细分析了其中2种估计算法:自相关矩阵奇异值分解法和M2M4估计法。对该2种算法的仿真计算结果表明:在低信噪比条件下,自相关矩阵奇异值分解法的准确性和稳定性优于M2M4估计法,而在信噪比较高时,自相关矩阵奇异值分解法的准确性略逊于M2M4法,但两者差异较小。在外场条件下,对截获到的较大脉宽脉冲应用该2种信噪比估计算法,结果表明:自相关矩阵奇异值分解法的SNR估计值与M2M4估计法接近,但方差更小,算法更加稳定,基本与仿真结果相吻合。

This paper firstly introduces several typical signal-to-noise ratio estimation algorithms,then detailedly analyzes two of the estimation algorithms：singular value decomposition of signal self-correlation matrix（SVD）and estimation method of secondary fourth-order moment（M2 M4）.Simulative calculation results show that the veracity and stability of SVD are better than that of M2 M4 under the condition of low signal to noise ratio（SNR）,while under the condition of rather high SNR,the veracity of SVD is a little bit lower than that of M2 M4,and the difference of the two is small.Results of out-field experiment on captured radar signals with relatively larger pulse widths show that the SNR estimation result from SVD is similar to the result from M2 M4 estimation method but with a lower variance,which indicates that the SVD algorithm is more stable,the results are basically identical to the simulation results.