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| Citation: | Zhao Qingchao, Zhang Yi, Wang Robert, Wang Wei, Wang Xiangyu. Signal Reconstruction Approach for Multichannel SAR in Azimuth Based on Multiframe Super resolution[J]. Journal of Radars, 2017, 6(4): 408-419. doi: 10.12000/JR17035
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Signal Reconstruction Approach for Multichannel SAR in Azimuth Based on Multiframe Super resolution
doi: 10.12000/JR17035
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Abstract
To achieve high-resolution wide-swath imaging, the use of multichannel techniques in azimuth is effective for spaceborne Synthetic Aperture Radar (SAR). For azimuth multichannel systems, the signal in azimuth is nonuniformly sampled if the uniform sampling condition related to Pulse Repetition Frequency (PRF) is not satisfied, which makes it important to reconstruct the azimuth signal prior to image formation. In this study, to solve the azimuth signal reconstruction problem in multichannel SAR, we propose the innovative use of a multiframe super-resolution method in Digital Image Processing (DIP) and summarize the general multiframe super-resolution process. Our simulation results and real data experiments verify the effectiveness of the proposed method, which demonstrates some advantages in complexity performance. By establishing linkages between the problem of signal reconstruction of nonuniformly sampled signals and the multiframe super-resolution concept, we provide a new approach to this traditional signal reconstruction problem. -
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References
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- Figure 1. Model for single image and multiframe super resolution
- Figure 2. Model and geometry for azimuth 3 channels system
- Figure 3. The sampling scenario of anazimuth 3 channels system
- Figure 4. Comparison of multiframe super resolution and signal reconstruction of multichannel SAR system
- Figure 5. Image degradation model with only geometric transformation considered
- Figure 6. Inverse of image (signal) degradation model
- Figure 7. General process for multiframe super-resolution
- Figure 8. Simulation results for the uniform sampling situation
- Figure 9. Simulation results for the nonuniform sampling situation
- Figure 10. Simulation results for the nonuniform sampling situation after reconstruction
- Figure 11. Partial enlarged drawing of the compression result in azimuth
- Figure 12. Acquisition method of the data for experiments
- Figure 13. The images obtained from the first channel and the unreconstructed nonuniform data
- Figure 14. The images obtained after signal reconstruction
- Figure 15. Zoomed azimuth cut of the point target in the image with both methods
- Figure 16. The realization of filter group method