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Open AccessArticle
Three-Dimensional Reconstruction of Partially Coherent Scatterers Using Iterative Sub-Network Generation Method
by
Xiantao Wang
Xiantao Wang ,
Zhen Dong
Zhen Dong *,
Youjun Wang
Youjun Wang ,
Xing Chen
Xing Chen and
Anxi Yu
Anxi Yu
College of Electronic Science and Technology, National University of Defense Technology, No. 109 De Ya Road, Changsha 410073, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(19), 3707; https://doi.org/10.3390/rs16193707 (registering DOI)
Submission received: 3 September 2024
/
Revised: 29 September 2024
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Accepted: 4 October 2024
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Published: 5 October 2024
Abstract
Synthetic aperture radar tomography (TomoSAR) has gained significant attention for three-dimensional (3D) imaging in urban environments. A notable limitation of traditional TomoSAR approaches is their primary focus on persistent scatterers (PSs), disregarding targets with temporal decorrelated characteristics. Temporal variations in coherence, especially in urban areas due to the dense population of buildings and artificial structures, can lead to a reduction in detectable PSs and suboptimal 3D reconstruction performance. The concept of partially coherent scatterers (PCSs) has been proven effective by capturing the partial temporal coherence of targets across the entire time baseline. In this study, an novel approach based on an iterative sub-network generation method is introduced to leverage PCSs for enhanced 3D reconstruction in dynamic environments. We propose a coherence constraint iterative variance analysis approach to determine the optimal temporal baseline range that accurately reflects the interferometric coherence of PCSs. Utilizing the selected PCSs, a 3D imaging technique that incorporates the iterative generation of sub-networks into the SAR tomography process is developed. By employing the PS reference network as a foundation, we accurately invert PCSs through the iterative generation of local star-shaped networks, ensuring a comprehensive coverage of PCSs in study areas. The effectiveness of this method for the height estimation of PCSs is validated using the TerraSAR-X dataset. Compared with traditional PS-based TomoSAR, the proposed approach demonstrates that PCS-based elevation results complement those from PSs, significantly improving 3D reconstruction in evolving urban settings.
Share and Cite
MDPI and ACS Style
Wang, X.; Dong, Z.; Wang, Y.; Chen, X.; Yu, A.
Three-Dimensional Reconstruction of Partially Coherent Scatterers Using Iterative Sub-Network Generation Method. Remote Sens. 2024, 16, 3707.
https://doi.org/10.3390/rs16193707
AMA Style
Wang X, Dong Z, Wang Y, Chen X, Yu A.
Three-Dimensional Reconstruction of Partially Coherent Scatterers Using Iterative Sub-Network Generation Method. Remote Sensing. 2024; 16(19):3707.
https://doi.org/10.3390/rs16193707
Chicago/Turabian Style
Wang, Xiantao, Zhen Dong, Youjun Wang, Xing Chen, and Anxi Yu.
2024. "Three-Dimensional Reconstruction of Partially Coherent Scatterers Using Iterative Sub-Network Generation Method" Remote Sensing 16, no. 19: 3707.
https://doi.org/10.3390/rs16193707
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