位场向下延拓的改进迭代维纳滤波法

根据维纳滤波理论导出的位场向下延拓滤波器为最佳下延滤波器，但因其实现需要已知待求位场和噪声的功率谱而在实际应用中受到限制.针对该问题，本文首先提出一种基于位场径向平均功率谱的位场噪声水平估计方法，进而利用偏差准则求取正则化参数，实现位场正则化向下延拓；然后将位场正则化下延结果的功率谱作为待求位场功率谱的估计初值，采用带修正项的迭代维纳滤波方法来更新对待求位场功率谱的估计，最后提出本文的位场向下延拓改进迭代维纳滤波方法.基于理论重力模型数据及航磁实测数据进行了向下延拓对比试验，结果表明，改进迭代法具有较好的收敛性，且下延精度优于Tikhonov正则化法和递增型维纳滤波法.

An improved iterative Wiener filter for downward continuation of potential fields

The downward continuation filter deduced by Wiener filter theory is an optimum downward continuation. However, the realization of the Wiener filter is difficult because it needs the power spectrum of the noise and the unknown potential field. In this paper, we propose an improved iterative Wiener filter for downward continuation of potential fields. Firstly, a noise level estimation method is proposed based on the radially averaged power spectrum of the potential field. Then, we use the discrepancy principle to choose the regularization parameter. Next, the regularization downward continuation result is used as the initial value of the iterative method. At last, an iterative Wiener filter with a correction term is used to update the power spectrum estimation of the unknown potential field. The comparison analysis of a theoretical gravity model and real aeromagnetic data shows that the proposed iterative method yields a better downward continuation than the Tikhonov regularization method and the incremental Wiener filter.