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A robust channel-calibration algorithm for multi-channel in azimuth HRWS SAR imaging based on local
Summary
A new robust channel-calibration algorithm improves high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) imaging by correcting channel mismatches. This method enhances Doppler ambiguity suppression for multi-channel SAR systems, leading to clearer images.
Area of Science:
- Remote Sensing
- Signal Processing
- Radar Technology
Background:
- High-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) is crucial for modern remote sensing.
- Multi-channel SAR systems address the resolution-frequency trade-off but face channel mismatch issues.
- Channel mismatch degrades Doppler ambiguity suppression in digital beamforming.
Purpose of the Study:
- To propose a robust channel-calibration algorithm for multi-channel in azimuth HRWS SAR imaging.
- To address performance losses caused by channel mismatch in Doppler ambiguity suppression.
- To enhance the quality of HRWS SAR images obtained from multi-channel systems.
Main Methods:
- A two-step channel-calibration algorithm based on weighted minimum entropy.
- Coarse-compensation pre-processing to correct timing uncertainty and range-invariant mismatches.
- Local maximum-likelihood weighted minimum entropy for residual range-dependent phase mismatch retrieval.
Main Results:
- The algorithm effectively corrects timing, amplitude, and phase mismatches.
- Residual range-dependent phase mismatches are accurately retrieved.
- Simulated and real airborne HRWS Scan-SAR data validate the algorithm's performance.
Conclusions:
- The proposed weighted minimum entropy algorithm offers a robust solution for channel calibration in multi-channel HRWS SAR.
- Effective correction of channel mismatches significantly improves Doppler ambiguity suppression.
- The approach demonstrates practical effectiveness for enhancing HRWS SAR imaging quality.
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