首页|Repeat-pass space-surface bistatic SAR tomography:accurate imaging and first experiment

Repeat-pass space-surface bistatic SAR tomography:accurate imaging and first experiment

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Space-surface bistatic synthetic aperture radar(SS-BiSAR)offers an additional observation angle for monostatic spaceborne SAR,making it a promising technology for high-accuracy deformation retrieval technology in local regions.Repeat-pass SS-BiSAR tomography can accurately estimate the surfaces of buildings and steep areas,effectively removing terrain phases during deformation retrieving.However,in-accuracies in the orbital ephemeris can lead to image geometry distortion,reducing image pair coherence,introducing interferometric phase errors,and consequently deteriorating tomographic precision.This pa-per precisely models the image geometry distortion and interferometric phase error caused by repeat-pass ephemeris error.We propose an ephemeris correction method based on the chirp-Z transform to address these issues.Furthermore,we introduce an accurate tomography model to improve 3D reconstruction accuracy.Our first SS-BiSAR tomography experiment,conducted using the Chinese Lutan-1 satellite,demonstrates that the correlation coefficient is improved by 0.16 after ephemeris error correction.Moreover,the density and precision of the tomographic point cloud are improved by 13.7%and 12.1%,respectively.

space-surface SARtomographyorbit errorimage distortionLutan-1

Zhiyang CHEN、Yuanhao LI、Cheng HU、Shenglei WANG、Xinpeng CHEN、Mihai DATCU、Andrea Virgilio MONTI-GUARNIERI

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Radar Technology Research Institute,School of Information and Electronics,Beijing Institute of Technology,Beijing 100081,China

Beijing Key Laboratory of Embedded Real-Time Information Processing Technology,Beijing Institute of Technology,Beijing 100081,China

Advanced Technology Research Institute,Beijing Institute of Technology,Jinan 250300,China

CEOSpaceTech,University Politehnica of Bucharest,Bucharest 050663,Romania

Dipartimento di Elettronica,Informazione e Bioingegneria,Politecnico di Milano,Milan 20133,Italy

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National Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNatural Science Foundation of Shandong Province

SO2022YFB3900055619602060096220105162101039ZR2022OF067

2024

中国科学:信息科学(英文版)
中国科学院

中国科学:信息科学(英文版)

CSTPCDEI
影响因子:0.715
ISSN:1674-733X
年,卷(期):2024.67(9)