机载串行双站斜视合成孔径雷达ELBF-CS成像算法

在机载串行双站斜视合成孔径雷达模型基础上，用收发载机多普勒贡献比为加权系数推导了点目标回波的扩展Loffeld频谱公式（ELBF）。以场景中心点目标双站扭曲项近似场景中各点目标双站扭曲项，再对频谱公式中剩余相位项做Taylor展开推导距离变标因子，构建了基于ELBF的串行机载双站斜视SAR的chirp scaling (CS)成像算法。算法在二维频域内补偿双站扭曲项，利用CS方法校正点目标距离徙动得到成像结果。考虑到双站回波距离空变性的影响，分析了宽场景成像数据距离向分块的准则。算法基于更高精度的点目标二维频谱公式，用CS方法提高成像效率，成像处理过程更简捷高效，最后通过仿真验证了算法在处理串行机载双站斜视SAR数据的有效性。 

Airborne Tandem Bistatic Squint SAR ELBF-CS Imaging Algorithm

Based on the model of the airborne tandem bistatic squint synthetic aperture radar (SAR), the extended Loffeld bistatic formula (ELBF) of point target echo is derived by using the weighting factors that is defined by Doppler contribution ratios of transmitter and receiver. Bistatic deformation (BD) term of all point targets (PT) within the imaging scene is substituted by the BD term of centre PT, and residual phase terms in ELBF are expanded using Taylor series expansion to derive the range scaling factor, then the chirp scaling (CS) imaging algorithm based on ELBF of tandem airborne bistatic squint SAR is established. To get accurate focusing result, the BD term is compensated in two-dimensional (2-D) frequency domain and range cell migration (RCM) is corrected by CS method. Considering of the space variance of echo data, data blocking rules in range for wide scene imaging is analyzed. The algorithm utilizes more accurate 2-D frequency spectrum formula, the imaging efficiency is improved by CS method, and the processing procedure is simplified as well. Simulations validate the proposed imaging algorithm to process the data of the tandem airborne bistatic squint SAR.