Title of article :
A very fast phase inversion approach for small baseline style interferogram stacks
Author/Authors :
Zhang، نويسنده , , Kui and Li، نويسنده , , Zhengzhou and Meng، نويسنده , , Guojie and Dai، نويسنده , , Yaqiong، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Pages :
8
From page :
1
To page :
8
Abstract :
The recently developed interferometric time-series analysis techniques have shown great potential in ground surface deformation monitoring applications. Such techniques overcome the drawbacks of the traditional differential radar interferometry (DInSAR) and can achieve millimeter-level measurement accuracy. One of the most important operations in interferometric time-series analysis techniques — referred to as phase inversion — is to estimate relative deformation velocity and digital elevation model error from a double-differenced interferometric phase time-series. Unfortunately, current phase inversion methods generally exhibit a low computational efficiency due to their high non-linearity, especially in the case when the dimension of an interferogram stack is large. In this paper, a new approach is proposed to efficiently resolve phase inversion problems defined on stacks constructed by interferograms with small baselines. The approach separates an estimation procedure into two parts. First, preliminary estimates are obtained by weighted least squares. Then, the estimates are refined by optimizing the corresponding ensemble phase coherence function. The proposed approach was applied to simulated and real data. Experimental results demonstrate that it can accurately address the phase inversion problem with a very high computational performance.
Keywords :
Derivative-based optimization , Weighted least squares , Interferometric time-series analysis , Satellite remote sensing , phase inversion , Interferometric synthetic aperture radar (InSAR)
Journal title :
ISPRS Journal of Photogrammetry and Remote Sensing
Serial Year :
2014
Journal title :
ISPRS Journal of Photogrammetry and Remote Sensing
Record number :
2229764
Link To Document :
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