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

机译:基于欠采样散射场数据的基于压缩感知原理的散射中心建模

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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窄带信号的散射中心建模。然而,为了获得TFR,对于大的电目标,方位角采样间隔应该非常小,这导致了大量的电磁计算。在散射波采样不足的情况下,TFR中会引起散射中心的多普勒曲线的混叠失真,这使得很难从TFR中估计相应散射中心的参数。为了解决这个问题,本文提出了一种基于欠采样散射波的散射中心建模方法。应用基于压缩感知原理的随机欠采样散射波来获取TFR散射中心的非混叠多普勒曲线。仿真结果验证了该方法的可行性。

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