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      3D Imaging for Array InSAR Based on Gaussian Mixture Model Clustering

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          Abstract

          Array InSAR can generate 3D point clouds with the use of SAR images of the observed scene, which are obtained using multiple channels in a single flight. Its resolution power in elevation enables one to solve the layover problem. However, due to the limited number of arrays and the short baseline length, the resolution power in elevation is restricted. Together with the layover phenomenon of the urban buildings, the result of 3D reconstruction suffers from poor accuracy in positioning, and it is difficult to extract the effective characteristics of the buildings. In view of this situation, this paper proposed a 3D reconstruction method of array InSAR based on Gaussian mixture model clustering. First, the 3D point clouds of the observed scene are obtained by an algorithm with super-resolution based on compressive sensing, and then the scatters of buildings are extracted by density estimation; after which the method of Gaussian mixture model clustering is used to classify the 3D point clouds of the buildings. Finally, the inverse SAR images of each region are obtained by using the system parameters, and the 3D reconstruction of the buildings is completed. Based on the actual data of the first domestic 3D imaging experiment by airborne array InSAR, the validity of the algorithm is confirmed and the 3D imaging results of the buildings are obtained.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 December 2017
          : 6
          : 6
          : 630-639
          Affiliations
          [1 ] ①(Science and Technology on Microwave Imaging Laboratory, Beijing 100190, China) ②(Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China) ③(University of Chinese Academy of Sciences, Beijing 100049, China)
          [2 ] ①(Science and Technology on Microwave Imaging Laboratory, Beijing 100190, China) ②(Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)
          Article
          a81c642563e44b89af5a70abfe993684
          10.12000/JR17020

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Categories
          Technology (General)
          T1-995

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