Abstract： During the construction of airborne Synthetic Aperture Radar (SAR) hardware systems, amplitude-phase errors are inevitably introduced in the transmit-receive channel links, which deteriorate the actual imaging performance of the SAR system. To address this issue, an amplitude-phase error compensation scheme for airborne SAR echo data based on internal calibration is designed, and imaging processing is completed in combination with an improved autofocus imaging algorithm. This scheme accurately estimates the amplitude-phase error values based on the reference, transmit, and receive calibration data in the internal calibration design, and compensates the echo data according to the amplitude-frequency and phase-frequency characteristics. Meanwhile, the traditional autofocus algorithm is improved by introducing quadratic phase terms, which enhances the estimation accuracy of high-order azimuth phase errors and optimizes the two-dimensional focusing effect of images. The processing results of measured data demonstrate that, after applying the proposed scheme, the range resolution improves by 6.6% and the azimuth resolution increases by 25.9%. Moreover, the ISLR meets the specified requirements of -10 dB and PSLR meets the specified requirements of -13 dB. Through the analysis of amplitude-phase error compensation and the comparative study of different imaging schemes, this research effectively enhances the image focusing accuracy, offering crucial guidance for the engineering implementation and practical applications of airborne SAR systems.
Key words : spaceborne synthetic aperture radar；airborne test platform；internal calibration；amplitude and phase errors；engineering verification
在传统 SAR 成像处理框架中，线性调频信号 (LFM) 通常被假定为理想信号模型，其回波数据仅考虑时延与幅度调制效应。然而，随着成像分辨率需求的持续提高，LFM 信号带宽不断拓展，致使信号幅频特性与相频特性难以维持理想状态。此外，SAR 系统发射与接收通道不可避免地引入幅相畸变误差，该类误差对 SAR 载荷成像质量形成显著制约。此外，机载平台运动的非平稳性会给 SAR 载荷运行带来运动误差。虽然高精度惯性测量单元（IMU）可实现部分误差补偿，但考虑到载荷的高采样频率特性，仍需依托自聚焦算法对高阶运动误差进行精准估计并补偿至 SAR 数据中，才能获得聚焦良好的 SAR 图像[6-7]。
针对幅相误差校正，文献[8]提出一种基于回波信号时域特征的相位估计与补偿算法，该算法通过分析图像强点目标特性实现回波数据的幅相误差补偿，但算法计算过程对地面目标场景存在依赖性，需对图像中的角反射器等强点目标进行信号提取与特征分析。在方位向高阶运动误差处理领域，相位梯度自聚焦（PGA）算法凭借其高效性与广泛适用性脱颖而出，该算法通过分析场景中多个特显点的多普勒频率偏移差异，实现相位误差的精确估计与补偿。但随着 SAR 影像分辨率的不断提升，传统一次或二次相位误差补偿已无法满足需求，对更高阶相位误差进行精确估计与补偿成为研究关键。
本文基于团队工程实践经验，在载荷设计阶段即前瞻性部署内定标模块，通过多模块定标数据协同分析与误差提取，实现了收发通道及信号源的幅相误差的有效补偿。同时，在信号处理环节对PGA算法进行适应性改进，显著提升了高阶相位误差的估计精度。研究成果为机载 SAR 系统的工程化验证提供了切实可行的技术方案与实践范例。
