电离层局部格网降分辨率层析方法

网格划分是电离层层析的重要一环,也是影响层析精度的重要因素之一。然而,现有研究更多地关注如何通过反演算法及模型来提高精度,较少关注格网划分这一手段。本文拟从格网划分这一角度来对电离层层析方法进行优化。先利用若干试验研究了格网分辨率与层像精度的关系,然后在此结论基础上提出了一种通过降低非感兴趣区域格网分辨率来提高感兴趣区域层像精度的方法。为验证本文方法的可行性,分别开展了两个不同的层析试验。两个试验同时表明:相对于传统的格网划分方法,本文方法在均方根误差、平均绝对误差、68%及95%百分位、标准差等多个精度指标上均具有优势。根据本文试验,利用本文方法均方根误差及平均绝对误差可望分别减少15%至40%。

Ionospheric tomography method by reducing grid resolution locally

The construction of the voxel model is an important part of computer ionospheric tomography (CIT) method. It will no doubt affect the accuracy of the CIT method. However, most existing researches focus on how to improve the image’s accuracy via inversion algorithm and few of them are concerned with the grid construction solution. This paper intends to improve accuracy by making some optimization on the voxel model. Some preliminary experiments were first carried out to explore the relationship between the accuracy of the image and its corresponding resolution. Then, based on the findings, a new CIT method, which is to improve the accuracy of the tomographic image of the interesting area at the price of reducing the resolution of the non-interesting area, was proposed. After that, some further experiments were taken to validate the new method. After comparing various accuracy indicators, such as root mean square error (RMSE), absolute mean error (MAE), 68% percentile, 95% percentile and stand deviation, the new method is showed to be better than the one that is not using the method proposed in this paper. According to our experiments, the new method is able to decrease RMSE/MAE of the tomographic image by 15% to 40%.