Array SAR technology,as a new type of 3D reconstruction technology,is an important direction for the development of InSAR.Due to the presence of high-frequency errors that are non-linear to the position of the point cloud,it is difficult to directly apply them to the production of surveying and mapping products.This article focuses on the characteristics of errors in array SAR point clouds.Firstly,noise is removed and point cloud matching is performed on the point cloud.Then,a linear refinement model is used for plane coordinates and a quadratic polynomial refinement model is used for elevation coordinate adjustment.By adding constraints on virtual observation values,a block adjustment model for array SAR point cloud data is constructed.Finally,two typical surface data types,which are mountainous and urban areas,are selected for experiments.The results show that the block adjustment model constructed in this paper can effectively reduce the high-frequency error impact in array SAR point cloud positioning,and the positioning accuracy and computational robustness are effectively improved under different control point conditions.
维普
万方数据