Advances in Information Extraction of Surface Parameters Using Tomographic SAR

Leida xuebao

卷:10

Changjun ZHAO¹  Lei HUANG¹  Ping ZHANG¹  Haiwei QIAO¹  Jianmin ZHOU¹  Zhen LI¹ 

[1] Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100094, China;

关键词: tomographic sar;    multi-baseline sar;    surface parameters;    vertical structure;    glacier thickness;    snow stratification;   

DOI  :  10.12000/JR20095

来源: DOAJ

【 摘 要 】

Traditional Synthetic Aperture Radar (SAR) imaging is the projection of a real three-dimensional scene onto a two-dimensional domain of azimuth and slant range, which results in the loss of the high-dimensional information. With the advancement of SAR system and its processing technology, tomographic SAR systems obtain multiple data along the height direction to construct the high-dimensional synthetic aperture, and use array signal processing methods to achieve high-resolution three-dimensional images. It can reconstruct the observation scene and extract vertical structure information of the ground target, which is very important for vegetation monitoring, snow and ice detecting, and urban modeling. This paper analyzed the key steps of three-dimensional imaging, such as image registration, flat-earth phase removal, phase compensation, and the three-dimensional focusing, as well as the current research status of each step based on the observation mechanism of tomographic SAR system. This paper particularly focuses on using tomographic SAR on the application of vegetation, glacier, snow, and urban information. The most relevant experimental results in the past two decades were introduced. Further, the application potential and existing problems related to the vegetation height with canopy structure, glacier thickness with internal structure, snow thickness with stratification, and urban three-dimensional reconstruction with deformation monitoring under different platforms are discussed. Finally, the prospects of TomoSAR in the primary applications field are presented.

【 授权许可】

Unknown