改进的基于最大似然估计的多通道InSAR高程重建方法

在通过InSAR技术获取地表数字高程模型(DEM)的应用中，为了提高该技术对大斜坡或突变等复杂地形的测绘能力，解决单基线情况下的高度模糊问题，可以利用多通道(多频率或多基线)InSAR技术实现。该文比较了最大似然估计法(ML)和最大后验概率估计法(MAP)的性能，并在最大似然估计法的基础上增加了坏点判断和加权均值滤波的环节，通过聚类分析和与相邻点的关系来判断目标像素是否为误差比较大的坏点，然后再利用加权均值滤波的方法将这些坏点剔除。这样，既保留了ML估计法速度快的特点，又提高了DEM的精度。仿真结果表明，在相同条件下，该方法既能保持较好的精度，同时又大大提高了算法的运行效率，非常有利于大规模数据的处理。

Improved Multichannel InSAR Height Reconstruction Method Based on Maximum Likelihood Estimation

In the application of getting the earth surfaces Digital Elevation Model (DEM) through InSAR technology, multichannel (multi-frequency or multi-baseline) InSAR technique can be employed to improve the mapping ability for complex areas with high slopes or strong height discontinuities, and solve the ambiguity problem which existed in the situation of single baseline. This paper compares the performance of Maxmum Likelihood (ML) estimation techniques with Maximum A Posteriori (MAP) estimation techniques, and adds two steps of bad pixels judgment and weighted filtering after the ML estimation. Bad pixels judgment is completed through cluster analysis and the relationship between adjacent pixels. A special weighted mean filter is used to remove the bad pixels. In this way, the advantage of the ML methods good efficiency is kept, and the accuracy of DEM also is improved. Simulation results indicate that this method can not only keep good accuracy but also improve greatly the computation efficiency under the same condition, which is advantageous for processing large scale of data sets.