一种基于内点罚函数和梯度迭代的频偏估计方法

Frequency Offset Estimation Method Based Oninternal Penalty Function and Gradient Iteration

为了克服现有技术的不足,提出了基于内点罚函数和梯度迭代的频偏估计方法。即利用频偏估计的方差与信噪比和相关训练段长度的关系式,在不缩小频偏估计范围的条件下,建立最小化频偏估计精度的方差的最优化函数问题,由于是非线性优化问题,采用内点惩罚函数法,在效用函数收敛于由频偏估计范围确定的相关长度的可行域之内时,通过梯度迭代,得到一个局部最小值,即最优相关训练段长度,实现相关训练段长度自适应信噪比的变化而调整,提高频偏估计的抗噪性和精度。

For overcoming the shortage of existing technique,put forward according to inside order to punish the function and the close together and related data segment of the frequency offset estimation.Make use of the variance of the frequency offset estimation to be partial to estimate of namely of the variance with believe the signal-to-noise ratio with the related data segment the relation type of the length.A selection criterion with the metric function is proposed.This proposed criterion utilizes internal penalty function and gradient iteration to maximize the metric function to reduce the variance.Under the conditions of adaptive signal-to-noise ratio changes,it is to realize the control of the autocorrelation complexity and improve the frequency offset estimation of the anti-noise and accuracy.