The nonlinear trajectory and bistatic characteristics of general bistatic synthetic aperture radar (SAR) can cause severe two-dimensional space-variance in the echo signal, and therefore it is difficult to focus the echo signal directly using the traditional frequency-domain imaging algorithm based on the assumption of azimuth translational invariance. At present, the state-of-the-art nonlinear trajectory imaging algorithm is based on singular value decomposition (SVD), which has the problem that SVD may be not controlled, and thus may lead to a high imaging complexity or low imaging accuracy. Therefore, this article proposes a nonlinear trajectory SAR imaging algorithm based on controlled SVD (CSVD). First, the chirp scaling algorithm is used to correct the range space-variance, and then SVD is used to decompose the remaining azimuth space-variant phase, and the first two feature components after SVD are integrated to make them be represented by a new feature component. Finally, the new feature component is used for interpolation to correct the azimuth space-variance. The simulation results show that the proposed CSVD can further improve the image quality compared with SVD-Stolt.

中文翻译：

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使用受控 SVD 算法处理具有非线性轨迹的双基地 SAR 数据

一般双基地合成孔径雷达（SAR）的非线性轨迹和双基地特性会导致回波信号存在严重的二维空间方差，因此传统的基于合成孔径雷达的频域成像算法难以直接聚焦回波信号。方位角平移不变性的假设。目前最先进的非线性轨迹成像算法是基于奇异值分解（SVD）的，存在奇异值分解可能不受控制的问题，从而可能导致成像复杂度高或成像精度低。因此，本文提出了一种基于受控SVD（CSVD）的非线性轨迹SAR成像算法。首先，使用chirp缩放算法来校正距离空间方差，然后用SVD分解剩余的方位空变相位，对SVD后的前两个特征分量进行积分，使它们由一个新的特征分量表示。最后，使用新的特征组件进行插值以校正方位角空间方差。仿真结果表明，与SVD-Stolt相比，所提出的CSVD可以进一步提高图像质量。