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Scattering center modelling based on compressed sensing principle from under-sampling scattering field data

机译:基于压缩传感原理的散射中心建模来自取样散射场数据

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It has been proved that scattering center modeling for narrow band signals can be achieved through the optimum image matching of time-frequency representation (TFR). In order to obtain TFR, however, the azimuth sampling interval should be quite small for electrically large target, which results in a huge amount of electromagnetic computation. Under the situation of under-sampling scattered waves, aliasing distortions of the Doppler curves of scattering centers will be caused in TFR, which makes it hard to estimate the parameters of corresponding scattering centers from TFR. To deal with this problem, an approach for scattering center modelling from under-sampling scattered waves are presented in this paper. The random under-sampling scattered waves based on the principle of compressive sensing are applied to acquire the non-aliasing Doppler curves of scattering centers in TFR. The feasibility of this method has been validated by the simulation results.
机译:已经证明,可以通过时频表示(TFR)的最佳图像匹配来实现用于窄带信号的散射中心建模。然而,为了获得TFR,方位采样间隔应该非常小,用于电大目标,这导致大量的电磁计算。在取样散射波的情况下,将在TFR中引起散射中心的多普勒曲线的混叠扭曲,这使得难以估计来自TFR的相应散射中心的参数。为了解决这个问题,本文提出了一种用于从采样的下面采样散射波散射中心建模的方法。基于压缩感测原理的随机欠采样散射波应用于在TFR中获取散射中心的非混溶多普勒曲线。该方法的可行性已通过模拟结果验证。

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