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
在傳統 SAR 成像處理框架中，線性調頻信號 (LFM) 通常被假定為理想信號模型，其回波數據僅考慮時延與幅度調制效應。然而，隨著成像分辨率需求的持續提高，LFM 信號帶寬不斷拓展，致使信號幅頻特性與相頻特性難以維持理想狀態。此外，SAR 系統發射與接收通道不可避免地引入幅相畸變誤差，該類誤差對 SAR 載荷成像質量形成顯著制約。此外，機載平臺運動的非平穩性會給 SAR 載荷運行帶來運動誤差。雖然高精度慣性測量單元（IMU）可實現部分誤差補償，但考慮到載荷的高采樣頻率特性，仍需依托自聚焦算法對高階運動誤差進行精準估計并補償至 SAR 數據中，才能獲得聚焦良好的 SAR 圖像[6-7]。
針對幅相誤差校正，文獻[8]提出一種基于回波信號時域特征的相位估計與補償算法，該算法通過分析圖像強點目標特性實現回波數據的幅相誤差補償，但算法計算過程對地面目標場景存在依賴性，需對圖像中的角反射器等強點目標進行信號提取與特征分析。在方位向高階運動誤差處理領域，相位梯度自聚焦（PGA）算法憑借其高效性與廣泛適用性脫穎而出，該算法通過分析場景中多個特顯點的多普勒頻率偏移差異，實現相位誤差的精確估計與補償。但隨著 SAR 影像分辨率的不斷提升，傳統一次或二次相位誤差補償已無法滿足需求，對更高階相位誤差進行精確估計與補償成為研究關鍵。
本文基于團隊工程實踐經驗，在載荷設計階段即前瞻性部署內定標模塊，通過多模塊定標數據協同分析與誤差提取，實現了收發通道及信號源的幅相誤差的有效補償。同時，在信號處理環節對PGA算法進行適應性改進，顯著提升了高階相位誤差的估計精度。研究成果為機載 SAR 系統的工程化驗證提供了切實可行的技術方案與實踐范例。
