Prediction-based phase unwrapping for differential interferograms of coal mining areas using a stochastic medium model

Xinpeng DiaoSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China;Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, ChinaCorrespondence[email protected]

http://orcid.org/0000-0002-1205-9304 View further author information

Kan WuSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China;Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, ChinaView further author information

Yuankun XuSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China;Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, ChinaView further author information

Dawei ZhouSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China;Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, ChinaView further author information

Ranli ChenDepartment of Surveying and Mapping, Shijiazhuang Institute of Railway Technology, Shijiazhuang, ChinaView further author information

ABSTRACT

This paper presents a novel phase unwrapping method for differential interferograms of coal mining areas, which takes full account of the mechanism of mining subsidence. The model uses a predicted deformation value for deformation caused by underground coal mining to assist the phase unwrapping and improve its accuracy. This method can overcome the defects of existing phase unwrapping algorithms that are not applicable to regions experiencing rapid deformation. The availability of the proposed method is first verified with noise-free simulated data, and then further tested with 3D laser scanning data and real synthetic aperture radar interferometry images. The results show that the prediction-based phase unwrapping method is able to realize phase unwrapping of differential interferograms covering coal mining areas that experience rapid deformation, and the results obtained are reasonable.

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Funding

This work was supported by the Fundamental Research Funds for the Central Universities under Grant number 2017BSCXB42

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Prediction-based phase unwrapping for differential interferograms of coal mining areas using a stochastic medium model

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Prediction-based phase unwrapping for differential interferograms of coal mining areas using a stochastic medium model

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