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AN ANALYTICAL FRAMEWORK FOR UNDERSTANDING PERSISTENT SCATTERER INCIDENCE IN INSAR IMAGERY WITH BANDWIDTH AND WAVELENGTH
被引:0
|作者:
Huang, Stacey
[1
]
Zebker, Howard A.
机构:
[1] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
关键词:
interferometric synthetic aperture radar (InSAR);
persistent scatterers;
probability distributions;
PERMANENT SCATTERERS;
RADAR INTERFEROMETRY;
SUBSIDENCE;
PRODUCT;
MODEL;
D O I:
10.1109/IGARSS39084.2020.9323173
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
With the increasing availability of spaceborne Synthetic Aperture Radar (SAR) imagery, Interferometric Synthetic Aperture Radar (InSAR) has become a prominent technique to study geophysical phenomena. However, its application can be limited in natural terrain due to rapid changes in the surface known as decorrelation. Persistent scatterers (PS) are stable elements that can be exploited in InSAR imagery to allow fine deformation mapping of the Earth's surface even in areas that are highly decorrelated. Despite the widespread use of PS techniques, little research has been dedicated to studying the relationship in between key system parameters and observed PS statistics. Such knowledge is critical in creating effective detection algorithms and informing design choices for satellite missions. Here, we present an analytical expression for the probability density function (PDF) of PS density with respect to system wavelength and bandwidth. This equation could be directly implemented in traditional detection algorithms for PS detection. We offer comparisons with real data, describing how the model could be improved. Further work will extend this expression to the probability of PS incidence and examine performance over different types of terrain.
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页码:2487 / 2490
页数:4
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