Modeling for InSAR orbit error based on time-varying polynomials to estimate DEM

doi:10.13474/j.cnki.11-2246.2024.0825

Abstract

Abstract: The existing digital elevation model update production mode is difficult to meet the urgent needs of real-life 3D and smart city information construction. InSAR repeat-pass technology is expected to achieve fast, large-scale, and high-precision DEM estimation through short-cycle revisit. However, in the repeat-pass mode, the severe time-varying orbital error is difficult to meet the requirements of high-precision mapping because the orbital error of the two SAR images is difficult to be offset by the interferometric process. Therefore, one of the key points of using repeat-pass InSAR technology to estimate DEM is how to reduce the influence of orbital error. Based on this, this paper proposes a method for estimating orbital error based on a time-varying polynomial model. This model constructs the functional relationship between the time-frequency baseline and the orbital error by block construction, and uses weighted least squares to achieve robust estimation. In order to verify the effectiveness of the proposed method, the data of L-band InSAR data in Hunan province are used for the first time to conduct tests, and InSAR DEM is estimated. In the two test sites, the experimental results verified the effectiveness and robustness of the proposed method and estimated the orbital error well. In addition, the accuracy of the DEM estimated by the proposed method is verified using satellite ICESat-2 data. The RMSE of the two test areas are 4.58 and 6.44 m, respectively, which are 48.8% and 52.9% higher than the traditional satellite method of removing orbital error to estimate DEM (8.94 and 13.68 m).

Key words: DEM, InSAR, time-varying orbital error, ICESat-2

CLC Number:

P237

PAN Ziyang, WAN Afang, WANG Feng, ZOU Mingpu, WEN Kangfeng, ZOU Meifang. Modeling for InSAR orbit error based on time-varying polynomials to estimate DEM[J]. Bulletin of Surveying and Mapping, 2024, 0(8): 145-150,176.

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