基于先验误差模型的机载高分宽幅DBF-SAR自聚焦算法

高分宽幅（HRWS）数字波束形成（DBF）合成孔径雷达（SAR）利用多通道空间采样代替部分时域采样，可以有效缓解SAR成像时高分辨率与宽测绘带间的矛盾，具有重要的军用和民用价值。现有常规DBF-SAR成像算法都假设雷达传感器相对位置精确已知，实际应用中受传感器位置测量误差影响，由位置不精确导致的相位误差会严重影响DBF-SAR高精度成像能力。在极坐标格式算法（PFA）框架下，推导了DBF-SAR成像处理后，残留相位误差的解析模型，分析了该误差对成像质量的影响。依据推导的先验相位误差解析结构模型，提出了一种基于图像对比度最优化准则的自聚焦算法。新算法通过引入先验相位结构信息，极大降低了待估参数的空间维数，可以同时改善自聚焦算法的参数估计精度和计算效率。数据处理结果验证了理论分析的正确性和所提算法的有效性。

Error model-aided autofocus for airborne high resolution wide swath DBF-SAR

The High-Resolution Wide-Swath (HRWS) Digital Beam Forming (DBF) Synthetic Aperture Radar (SAR) operates with multi-channel spatial sampling instead of partial time-domain sampling, effectively easing the contradiction between high resolution and wide swath of SAR images, exhibiting important military and civilian values. Conventional DBF-SAR imaging methods assume that the relative position of the radar sensor is accurately known. However, phase errors caused by inaccurate sensor positions will seriously affect the high-resolution imaging capability of the DBF-SAR. Based on the Polar Format Algorithm (PFA), the analytical model of the residual azimuth phase error after DBF-SAR imaging processing is derived, and the effect of the error on the imaging quality is analyzed. An autofocusing algorithm based on image contrast optimization is proposed with the deduced analytical structure model of a priori phase errors. This method reduces the spatial dimension of the parameters to be estimated, improving the parameter estimation accuracy and calculation efficiency of the autofocus algorithm by introducing a priori analytical structure information. Simulation data processing results verify the correctness of theoretical analysis and the effectiveness of the proposed method.