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Bistatic forward-looking SAR imaging processing based on optimized NLCS algorithm

机译:基于优化NLCS算法的双基地前视SAR成像处理

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In bistatic forward-looking SAR, due to its special motion model, the inevitable non-ideal motion error is introduced into the radar echo signal. Resulting in unknown two-dimensional space-varying RCM and Doppler parameters in the target echo. This paper proposes an optimization based NLCS method. Firstly, the first-order RCM is corrected by the keystone transform. Then based on the minimum entropy criterion and the processing idea of NLCS algorithm, the problem of unknown space-varying bending correction and Doppler parameter equalization is transformed into a constrained optimization problem. The genetic algorithm is used to solve the optimal NLCS equilibrium parameters. Thereby achieving high-precision imaging processing of bistatic forward-looking SAR echoes.
机译:在双基地前视SAR中,由于其特殊的运动模型,不可避免的非理想运动误差被引入雷达回波信号中。在目标回波中导致未知的二维时空RCM和多普勒参数。本文提出了一种基于优化的NLCS方法。首先,通过梯形失真校正对一阶RCM进行校正。然后基于最小熵准则和NLCS算法的处理思想,将未知时空弯曲校正和多普勒参数均衡问题转化为约束优化问题。遗传算法被用来求解最佳的NLCS平衡参数。从而实现双基地前视SAR回波的高精度成像处理。

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