Residual Low-Order Phase-Error Estimation and Compensation for Post-Autofocus UAV K-Band Multi-Baseline InSAR

This study examines residual low-order (linear and constant) phase errors in interferometric synthetic aperture radar (InSAR) when compact, high-frequency radar sensors are mounted on commercial uncrewed aerial vehicles (UAVs). Although higher carrier frequencies and shorter standoff ranges enable fine-resolution interferometry, the same characteristics—together with UAV platform instability—make the system highly vulnerable to motion-induced phase errors, which can significantly degrade or even invalidate DEM reconstruction. This paper first quantifies the admissible motion-error bounds for reliable multi-baseline phase-gradient estimation, and then introduces a post-autofocus correction scheme that estimates the residual linear term from the interferometric fringe frequency and refines it via an FFT-based correlation objective, while the constant term is calibrated using ground control points (GCPs). The method is validated through simulations of a 24 GHz UAV demonstrator. To the best of our knowledge, this work provides the first post-autofocus demonstration of linear-and-constant residual-error mitigation for UAV-based high-frequency multi-baseline InSAR. In the considered K-band setting, the proposed approach reduces the DEM error from 42 m to 0.2 m (≈98% improvement).

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Publication Details

Journal
Mathematics
Published
2026-02-25
DOI
https://doi.org/10.3390/math14050772
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
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article

Residual Low-Order Phase-Error Estimation and Compensation for Post-Autofocus UAV K-Band Multi-Baseline InSAR

Yaxuan Li, Xiao Zhou, Bin Wen
Mathematics
Synthetic Aperture Radar (SAR) Applications and Techniques
article

Residual Low-Order Phase-Error Estimation and Compensation for Post-Autofocus UAV K-Band Multi-Baseline InSAR

Yaxuan Li, Xiao Zhou, Bin Wen
article en

Abstract

This study examines residual low-order (linear and constant) phase errors in interferometric synthetic aperture radar (InSAR) when compact, high-frequency radar sensors are mounted on commercial uncrewed aerial vehicles (UAVs). Although higher carrier frequencies and shorter standoff ranges enable fine-resolution interferometry, the same characteristics—together with UAV platform instability—make the system highly vulnerable to motion-induced phase errors, which can significantly degrade or even invalidate DEM reconstruction. This paper first quantifies the admissible motion-error bounds for reliable multi-baseline phase-gradient estimation, and then introduces a post-autofocus correction scheme that estimates the residual linear term from the interferometric fringe frequency and refines it via an FFT-based correlation objective, while the constant term is calibrated using ground control points (GCPs). The method is validated through simulations of a 24 GHz UAV demonstrator. To the best of our knowledge, this work provides the first post-autofocus demonstration of linear-and-constant residual-error mitigation for UAV-based high-frequency multi-baseline InSAR. In the considered K-band setting, the proposed approach reduces the DEM error from 42 m to 0.2 m (≈98% improvement).

MathematicsVol. 14(5)
Beijing Institute of Technology (CN), North China Institute of Aerospace Engineering (CN), University of Birmingham (GB)
Openalex Percentile: Top 44%
Synthetic Aperture Radar (SAR) Applications and Techniques
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