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Sub-Nyquist Sampling and Parameters Estimation of Wideband LFM Signals Based on FRFT

机译:基于FRFT的宽带LFM信号亚奈奎斯特采样和参数估计

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摘要

Last years, most sub-Nyquist sampling and parameters estimation methods for linear frequency modulated (LFM) signals are based on compressed sensing (CS) theory. However, nearly all CS reconstruction algorithms are with high computational complexity and difficult to be implemented in hardware. In this paper, a novel framework of sub-Nyquist sampling and low-complexity parameters estimation for LFM signals is proposed. The incoherent sampling in CS theory is introduced into the construction of sub-Nyquist sampling system, but no CS reconstruction algorithm is employed in the estimation of parameters. Based on the energy aggregation of LFM signals in the proper fractional Fourier transform (FRFT) domain, the chirp rate and center frequency can be estimated by linear operations. Accordingly, the proposed estimation method is easily realized compared with existing estimation methods based on CS. Simulation results verify its effectiveness and accuracy.
机译:近年来,大多数用于线性调频(LFM)信号的次奈奎斯特采样和参数估计方法都是基于压缩感测(CS)理论的。但是,几乎所有CS重建算法都具有很高的计算复杂度,并且很难在硬件中实现。在本文中,提出了一种新的子奈奎斯特采样和低复杂度参数估计的框架。 CS理论中的非相干采样被引入亚奈奎斯特采样系统的构造中,但是在参数估计中未采用CS重建算法。基于适当的分数阶傅立叶变换(FRFT)域中LFM信号的能量聚集,可以通过线性运算来估计线性调频率和中心频率。因此,与现有的基于CS的估计方法相比,所提出的估计方法容易实现。仿真结果验证了其有效性和准确性。

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