The rigid oscillation and flexible deformation baseline errors occur in dual-antenna unmanned aerial vehicle (UAV) SAR interferometry (InSAR). The errors caused by airflow disturbances and UAV platform mechanical oscillation will lead to interferometric phase undulation. Measuring the errors has high requirements for length and time accuracy for the equipment. In this paper, a time-varying baseline error (TBE) estimation and compensation method based on continuous time-domain subaperture data is proposed. Firstly, we model the TBE and derive its expression in each subaperture image focused by the chirp scaling dechirp (CS-dechirp) algorithm. Then it is possible to extract the estimated differential TBE (D-TBE) from the differential interferogram of overlapping scenes in subaperture images. Further, the full-aperture TBE can be obtained through an integration of the estimated D-TBE. Finally, the full-aperture compensation can be accomplished by a phase correction after the range variation estimation. Taking advantage of the time-domain subaperture, the D-TBE phases are sampled at each subaperture center time, and the proposed method can be well combined with a motion compensation algorithm in the processing flow for UAV InSAR. Furthermore, the case of low coherence is overcome. The results of simulation and real measured airborne single-pass dual-antenna data validate the proposed approach.

中文翻译：

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基于原始雷达数据时域子孔径的无人机SAR干涉测量时变基线误差估计与补偿


双天线无人机SAR干涉测量(InSAR)会出现刚性振荡和柔性变形基线误差。气流扰动和无人机平台机械振荡引起的误差会导致干涉相位波动。测量误差对设备的长度和时间精度要求很高。本文提出了一种基于连续时域子孔径数据的时变基线误差（TBE）估计和补偿方法。首先，我们对 TBE 进行建模，并推导其在通过线性调频缩放 dechirp (CS-dechirp) 算法聚焦的每个子孔径图像中的表达式。然后可以从子孔径图像中重叠场景的微分干涉图中提取估计的微分TBE（D-TBE）。此外，通过对估计的D-TBE进行积分可以得到全孔径TBE。最后，在距离变化估计之后，可以通过相位校正来完成全孔径补偿。利用时域子孔径的优势，在每个子孔径中心时间对D-TBE相位进行采样，该方法可以与无人机InSAR处理流程中的运动补偿算法很好地结合。此外，还克服了低相干性的情况。仿真结果和实测机载单通双天线数据验证了所提出的方法。