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| Citation: | Liu Huayou, Zheng Mingjie, Zhang Heng, Wang Yu, Qin Xiaofang. An Effective Method of Airborne Dual-frequency Interferometric Terrain Elevation Reconstruction[J]. Journal of Radars, 2018, 7(4): 475-486. doi: 10.12000/JR18013
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An Effective Method of Airborne Dual-frequency Interferometric Terrain Elevation Reconstruction
doi: 10.12000/JR18013
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Abstract
Dual-frequency joint phase unwrapping does not need to satisfy the Iton hypothesis, so dual-frequency interferometry can effectively extract elevation information from large terrain undulation areas. This paper presents an effective method for Dual-Frequency Interferometry (DFI) SAR terrain elevation reconstruction, aiming at the low precision of elevation reconstruction in DFI processing. This method improves the key steps in the conventional process. Firstly, Nonlocal Interferogram Estimation (NL-InSAR) technique is used to accurately estimate amplitude map, coherence coefficient, and Interferometric phase before the registration in different bands. After filtering, the filtered amplitude information of each band is used to realize the registration of Interferometric phase in different bands. Then clustering analysis technique is used to mark the effective points and noise points of unwrapping phase, and these effective points are used to filter the mean value of joint phase unwrapping. The airborne measured data used in the experiment include the complex data of C band and X band main and auxiliary SAR images of the same scene. In view of the measured data processing, the proposed method provides better results of elevation reconstruction. -
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References
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- Figure 1. Improved processes of dual-frequency interferometry
- Figure 2. Three interferometric phase images after registration
- Figure 3. The two flattened interferograms removed flat-Earth phase
- Figure 4. Contrast between interferogram before filtering and filtered interferogram
- Figure 5. Contrast between SAR image before filtering and filtered SAR image
- Figure 6. Contrast between coherence coefficient image before filtering and filtered coherence coefficient image
- Figure 7. Comparison of different band amplitude graphs before NL-InSAR filtering
- Figure 8. Comparison of different band amplitude graphs after NL-InSAR filtering
- Figure 9. Comparison of the distribution histogram of correlation coefficients of different bands before and after NL-InSAR filtering
- Figure 10. The unwrapped phase images unwrapped by diffenent algorithms
- Figure 11. The residual error images of different algorithms
- Figure 12. Flow chart of effective point and noise marking
- Figure 13. Histogram distribution of ambiguity vector summation
- Figure 14. Contrast between clustering Mean filter resultand traditional mean filter result
- Figure 15. Contrast between clustering mean filter result and traditional mean filter result in area A
- Figure 16. The scene of processing data
- Figure 17. Interferograms after registration of different bands
- Figure 18. The single-channel phase unwrapped by MCF algorithm
- Figure 19. The dual-frequency phase unwrapped by ML algorithm
- Figure 20. The dual-frequency phase unwrapped by TV-MAP and cluster mean filter
- Figure 21. Contrast between single-band unwrapped phase and dual-frequency combined uwrapped phase
- Figure 22. The airborne double-frequency rebuilding DEM