小数据集PS-DInSAR的PS点探测研究

PS点的探测是PS-DInSAR监测地表形变的前提。针对现有PS点探测方法在小数据集条件下误选率高、合理性低等问题，本文综合考虑PS点的强散射和稳定性，提出了振幅阈值预选的迭代综合相干系数PS探测方法，首先通过振幅阈值完成PS点的预选，然后利用迭代综合相干系数法精选出PS点。以上海地区的23幅ERS SAR图像作为实验对象，对比分析了几种方法在不同数据量下探测PS点分布、误选率以及合理性。理论分析及实验结果表明，本文方法对于小数据集PS点的探测具有明显优势，在PS点分布、误选率以及探测合理性方面都优于其他方法，将其用于实际区域形变速率反演，与实际统计资料仅相差1.2717 mm/a，说明结果准确、可靠性高。 

Method on PS Detection of Small Dataset PS-DInSAR

PS detection is the premise of deformation monitoring using PS-DInSAR. Considering strong scattering and stability of PS pixels, this paper proposed a new PS selection method using amplitude threshold and iterative comprehensive coherent coefficient to solve the problems of existing methods such as inapplicability for small dataset. Firstly, PS candidates (PSCs) were selected using amplitude threshold. Then, the true PS pixels were selected by iterative comprehensive coherent coefficient method. The distribution, error rate and precision under different amount of images of several methods were contrasted and analyzed using 23 ERS SAR images covering Shanghai. Theoretical analysis and experimental result show that the proposed method has evident advantages for PS selection of small data set and performs better in the matter of PS distribution, error rate and rationality. The subsidence velocity error between the result of this paper and real measured data is only 1.2717 mm/a, which is precise and credible.