Channel Amplitude and Phase Error Estimation of Fully Polarimetric Airborne SAR with 0.1 m Resolution

In order to achieve 0.1 m resolution and fully polarimetric observation capabilities for airborne SAR systems, the adoption of stepped-frequency modulation waveform combined with the polarization time-division transmit/receive (T/R) technique proves to be an effective technical approach. Considering the issue of range resolution degradation and paired echoes caused by multichannel amplitude–phase mismatch in fully polarimetric airborne SAR with 0.1 m resolution, an amplitude–phase error estimation algorithm based on echo data is proposed in this paper. Firstly, the subband amplitude spectrum correction curve is obtained by the statistical average of the subband amplitude spectrum. Secondly, the paired-echo broadening function is obtained by selecting high-quality sample points after single-band imaging and the nonlinear phase error within the subbands is estimated via Sinusoidal Frequency Modulation Fourier Transform (SMFT). Thirdly, based on the minimum entropy criterion of the synthesized compressed pulse image, residual linear phase errors between subbands are quickly acquired. Finally, two-dimensional cross-correlation of the image slice is utilized to estimate the positional deviation between polarization channels. This method only requires high-quality data samples from the echo data, then rapidly estimates both intra-band and inter-band amplitude/phase errors by using SMFT and the minimum entropy criterion, respectively, with the characteristics of low computational complexity and fast convergence speed. The effectiveness of this method is verified by the imaging results of the experimental data.

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Publication Details

Journal
Remote Sensing
Published
2025-08-04
DOI
https://doi.org/10.3390/rs17152699
Citations
2
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
9.99
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article

Channel Amplitude and Phase Error Estimation of Fully Polarimetric Airborne SAR with 0.1 m Resolution

Jianmin Hu, Guangyou Fang, Huanjun Chen, Xinwen Zhang et al.
2 citations
Remote Sensing
Synthetic Aperture Radar (SAR) Applications and Techniques
9.99
article

Channel Amplitude and Phase Error Estimation of Fully Polarimetric Airborne SAR with 0.1 m Resolution

Jianmin Hu, Guangyou Fang, Huanjun Chen, Xinwen Zhang, Yanfei Wang, Yan Shen, Zhenyu Yang, Jinpeng Xie
article en
2 citations

Abstract

In order to achieve 0.1 m resolution and fully polarimetric observation capabilities for airborne SAR systems, the adoption of stepped-frequency modulation waveform combined with the polarization time-division transmit/receive (T/R) technique proves to be an effective technical approach. Considering the issue of range resolution degradation and paired echoes caused by multichannel amplitude–phase mismatch in fully polarimetric airborne SAR with 0.1 m resolution, an amplitude–phase error estimation algorithm based on echo data is proposed in this paper. Firstly, the subband amplitude spectrum correction curve is obtained by the statistical average of the subband amplitude spectrum. Secondly, the paired-echo broadening function is obtained by selecting high-quality sample points after single-band imaging and the nonlinear phase error within the subbands is estimated via Sinusoidal Frequency Modulation Fourier Transform (SMFT). Thirdly, based on the minimum entropy criterion of the synthesized compressed pulse image, residual linear phase errors between subbands are quickly acquired. Finally, two-dimensional cross-correlation of the image slice is utilized to estimate the positional deviation between polarization channels. This method only requires high-quality data samples from the echo data, then rapidly estimates both intra-band and inter-band amplitude/phase errors by using SMFT and the minimum entropy criterion, respectively, with the characteristics of low computational complexity and fast convergence speed. The effectiveness of this method is verified by the imaging results of the experimental data.

Remote SensingVol. 17(15)
Sun Yat-sen University (CN), Chinese Academy of Sciences (CN), Key Laboratory of Guangdong Province (CN), Aerospace Information Research Institute (CN)
Openalex Percentile: Top 2%
Synthetic Aperture Radar (SAR) Applications and Techniques
9.99
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