Amplitude-Optimized UZH for Polarimetric Channel Imbalance Calibration in PolSAR Data.

IEEE Trans. Geosci. Remote. Sens.(2023)

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摘要
Nowadays, non-corner reflector (CR) calibration techniques are attractive to relieve the workload of polarimetric calibration. Yet, it is challenging to derive the complex co-pol channel imbalance (CCI) precisely and conveniently when CRs are unavailable. Our previous research provided the general unitary zero helix (gUZH) and phase-optimized UZH (pUZH) methods to estimate CCI by the bare soil pixels. However, the amplitude is still overestimated compared with CRs. Thus, this article proposes to optimize the goal function by L2 normalization and derive the amplitude-optimized UZH (aUZH) to estimate the CCI amplitude robustly. The new aUZH performs well in resisting errors from improper reference picking. We also develop a signal-to-noise ratio (SNR) filter that selects the soil pixels with high SNR into aUZH to reduce the influence of the noise floor. Furthermore, we combine aUZH and the SNR filter to develop a method, i.e., HybridC, to process the massive data for a more precise solution. This article validates the new algorithm through the external calibration of the Gaofen-3 satellite from 2017 to 2020. The result shows that CR error in HH/VV is better than 0.26 dB after aUZH calibration. Furthermore, we process the proposed HybridC as a tool to monitor the sensor quality of the Gaofen-3 in over 40 000 images. We find that the imbalance phase exceeds the designed specification at some beams, and our algorithm can calibrate the bias precisely.
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关键词
Calibration, Distortion, Vegetation mapping, Soil, Scattering, Media, Additive noise, Gaofen-3, image quality, polarimetric calibration (PolCal)
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