Precise and Automatic 3-D Absolute Geolocation of Targets Using Only Two Long-Aperture SAR Acquisitions

被引:4
作者
Duque, Sergi [1 ]
Parizzi, Alessandro [2 ]
De Zan, Francesco [2 ]
机构
[1] Magna Elect Europe GmbH & Co OHG, D-80807 Munich, Germany
[2] German Aerosp Ctr DLR, Remote Sensing Technol Inst IMF, D-82234 Wessling, Germany
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2019年 / 57卷 / 08期
关键词
3-D point cloud; crossing orbit; high resolution; satellite geodesy; stereogrammetry; synthetic aperture radar (SAR); target matching; urban digital elevation model (DEM); zenith path delay (ZPD) estimation; LEVEL RANGING ACCURACY; TERRASAR-X; SCATTERERS; LIMITS;
D O I
10.1109/TGRS.2019.2899167
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
This paper deals with precise absolute geolocation of point targets by means of a pair of high-resolution synthetic aperture radar (SAR) acquisitions, acquired from a satellite. Even though a single SAR image is a 2-D projection of the backscatter, some 3-D information can be extracted from a defocussing analysis, depending on the resolution, thanks to orbital curvature. A second acquisition, observing the same scene under a different look angle, adds stereogrammetric capability and can achieve geolocation accuracy at decimeter level. However, for the stereogrammetric analysis to work, it is necessary to match targets correctly in the two images. This task is particularly difficult if it has to be automatic and targets are dense. Unfortunately, the defocussing-based geolocation is not sufficient for reliable target matching: the limiting factor is the unknown tropospheric delay that can cause geolocation errors of several meters in the elevation direction. However, observing that the tropospheric phase screen displays a low-pass character, this paper shows how to identify statistically the local atmospheric disturbances, therefore dramatically improving the score of successful matching. All steps involved exploit peculiar radar image characteristics and, thanks to this, avoid generic point cloud matching algorithms. The proposed algorithm is shown at work on a pair of TerraSAR-X staring spotlight images.
引用
收藏
页码:5395 / 5406
页数:12
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