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Sparse passive radar imaging based on FM stations using the U-ESPRIT for moving target

机译:使用U-ESPRIT的基于FM电台的稀疏无源雷达成像用于移动目标

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This paper studies the passive radar imaging system based on Frequency Modulated (FM) stations. Firstly, we establish the imaging model for moving target which consists of multiple FM stations and one receiver. Although movement information brings improvement of resolution, similarly to ISAR, but the shortage of wavenumber domain filling also causes the failure in imaging under little stations condition, so we consider using the sparse recovery techniques to realize imaging. However, in actual radar system, some previous CS methods probably suffer from off-grid point effect, which causes performance degradation of the methods. Therefore, based on the theories of Xampling and the finite rate of innovation (FRI), we propose a high-resolution sparse imaging method to overcome the problems stated above, which utilizes the unitary estimating signal parameters through rotational invariance techniques (U-ESPRIT) and the cross point searching technique (CPST). Simulation results show the effectiveness of the proposed method and the related analysis.
机译:本文研究了基于调频电台的无源雷达成像系统。首先,我们建立了由多个FM电台和一个接收器组成的移动目标的成像模型。尽管运动信息带来了分辨率的提高,与ISAR类似,但是波数域填充的不足也导致在小站位条件下成像失败,因此我们考虑使用稀疏恢复技术来实现成像。然而,在实际的雷达系统中,某些先前的CS方法可能会受到离网点效应的影响,这会导致方法的性能下降。因此,基于Xampling和有限创新率(FRI)的理论,我们提出了一种高分辨率的稀疏成像方法来克服上述问题,该方法利用旋转不变技术(U-ESPRIT)来统一估计信号参数以及交叉点搜索技术(CPST)。仿真结果表明了所提方法和相关分析的有效性。

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