A Denoising Algorithm for InSAR Surface Deformation Application
This letter describes an order-statistical based interferometry synthetic aperture radar (InSAR) phase estimation algorithm for surface deformation. Critical interferometry issues during deformation measurement (which covers inevitable noises, undersampling due to high topography variation and wrapped phase condition) are presented. This algorithm is mainly emphasizes on InSAR geometry modelling, deformation value extraction, and the most typical part of phase estimation process. A phase estimation method based on improved order-statistical filter is employed to overcome aforementioned interferometry issues. External digital elevation map is employed into differential-InSAR approach to extract the deformation information from interferogram by eliminating phase variation due to topography. Final processing outcome of the order-statistical based InSAR algorithm is a surface deformation image due to two observations. For comparative studies, the order-statistical based method and two other InSAR phase estimation algorithms are implemented via computer simulation (where evaluation metric of root mean square error RMS is introduced for performance assessment). The order-statistical based InSAR phase estimation method is also validated by true data set of satellite measurement.
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Document Type: Research Article
Affiliations: Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama 75450 Melaka, Malaysia
Publication date: November 1, 2017
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