基于α-随机解调器的线性调频信号模拟信息转换方法
Analog-to-information conversion based on α-random demodulator for linear frequency modulated signals
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摘要: 针对宽带线性调频信号的采集、存储和传输困难问题,提出了一种基于α-随机解调器的线性调频信号模拟信息转换方法,有效降低信号采集频率与采样点数。首先,根据线性调频信号特点,提出了α-随机解调器的系统模型,用以完成对线性调频信号的压缩采样。然后,分析了α-随机解调器工作过程,建立了系统采样点与原始输入信号稀疏系数之间的联系,进而建立了α-随机解调器压缩观测数学模型。基于该模型,分析了稀疏系数精确重构条件以及原始信号重构模型。最后,通过引入基于凸优化的信号重构算法,实现了对原始信号的准确重构。仿真与实测实验结果表明,本文基于α-随机解调器的模拟信息转换方法能够有效实现线性调频信号的压缩采样与准确重构。
Abstract: In order to solve the problem of acquisition, storage and transmission for linear frequency modulated (LFM) signals, a novel analog-to-information conversion method based on α-random demodulator is proposed. With the proposed system, both the sampling frequency and sample number can be reduced significantly during the compressive sampling. Utilizing the sparsity of LFM signals in fractional Fourier domain, the compressive sampling process was achieved by the proposed α-random demodulator. Then, we analyzed the working process for α-random demodulator systematically. The relationship between system output and sparse vector of LFM signals was presented. And based on this relationship, we further established the mathematical reconstruction model for α-random demodulator to reconstruct the sparse vector of LFM signals. Finally, the reconstruction was achieved by solving the convex optimization problem. And the accurate reconstruction for original signals is obtained. The effectiveness of the proposed scheme was verified by numerical experiments. We show that the proposed analog-to-information conversion method achieves the effective compressive sampling and accurate reconstruction for LFM signals. Compared with the other analog-to-information conversion methods, we reduced the complexity of dictionary construction during the reconstruction process.