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| Citation: | QIU Xiaolan, JIAO Zekun, PENG Lingxiao,
et al. SARMV3D-1.0: Synthetic aperture radar microwave vision 3D imaging dataset[J].
Journal of Radars, 2021, 10(4): 485–498. doi: 10.12000/JR21112
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SARMV3D-1.0: Synthetic Aperture Radar Microwave Vision 3D Imaging Dataset（in English）
DOI: 10.12000/JR21112
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Abstract
Three-dimensional (3D) imaging is one of the leading trends in the development of Synthetic Aperture Radar (SAR) technology. The current SAR 3D imaging system mainly includes tomography and array interferometry, both with drawbacks of either long acquisition cycle or too much system complexity. Therefore, a novel framework of SAR microwave vision 3D imaging is proposed, which is to effectively combine the SAR imaging model with various 3D cues contained in SAR microwave scattering mechanism and the perceptual semantics in SAR images, so as to significantly reduce the system complexity, and achieve high-efficiency and low-cost SAR 3D imaging. In order to promote the development of SAR microwave vision 3D imaging theory and technology, a comprehensive SAR microwave vision 3D imaging dataset is planned to be constructed with the support of NSFC major projects. This paper outlines the composition and construction plan of the dataset, and gives detailed composition and information description of the first version of published data and the method of making the dataset, so as to provide some helpful support for SAR community. -
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References
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- Figure 1. Composition of SARMV3D dataset
- Figure 2. Composition of SARMV3D-BIS dataset
- Figure 3. Flow chart of construction of SARMV3D-BIS dataset
- Figure 4. Extraction of building footprint
- Figure 5. Schematic diagram of building roof
- Figure 6. Projection of building elevation
- Figure 7. Schematic diagram of equivalent mirror point
- Figure 8. Projection of building shadow in SAR image
- Figure 9. Projection of multiple buildings in SAR image
- Figure 10. Loss curve in the train process on the SARMV3D-BIS 1.0(S) validation set by using Mask RCNN
- Figure 11. Results of instance segmentation on the SARMV3D-BIS 1.0(S) validation set by using Mask RCNN
- Figure 12. Amplitude image of GOTCHA dataset
- Figure 13. Array InSAR
- Figure 14. Data of Yuncheng area
- Figure 15. Data of mount Emei area
- Figure 16. Comparison of 3D point cloud results
- Figure 17. Results of phase error estimation between channels
- Figure 18. Comparison results of two phase estimation methods
- Figure 19. 3D imaging results of SARMV3D Imaging dataset
- Figure 20. Overlay times map of SARMV3D Imaging dataset
- Figure 1. Release webpage of Synthetic Aperture Radar Microwave Vision 3D Imaging Dataset
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