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Compressive Sampling for Efficient Astrophysical Signals Digitizing: From Compressibility Study to Data Recovery

机译:压缩采样有效数字化的天体信号:从可压缩性研究到数据恢复

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The design of a new digital radio receiver for radio astronomical observations in outer space is challenged with energy and bandwidth constraints. This paper proposes a new solution to reduce the number of samples acquired under the Shannon–Nyquist limit while retaining the relevant information of the signal. For this, it proposes to exploit the sparsity of the signal by using a compressive sampling process (also called Compressed Sensing (CS)) at the Analog-to-Digital Converter (ADC) to reduce the amount of data acquired and the energy consumption. As an example of an astrophysical signal, we have analyzed a real Jovian signal within a bandwidth of 40MHz. We have demonstrated that its best sparsity is in the frequency domain with a sparsity level of at least 10% and we have chosen, through a literature review, the Non-Uniform Sampler (NUS) as the receiver architecture. A method for evaluating the reconstruction of the Jovian signal is implemented to assess the impact of CS compression on the relevant inf...
机译:用于外层空间射电天文观测的新型数字无线电接收机的设计面临着能量和带宽的限制。本文提出了一种新的解决方案,以减少在Shannon–Nyquist限制下采集的样本数量,同时保留信号的相关信息。为此,它建议通过在模数转换器(ADC)上使用压缩采样过程(也称为压缩感测(CS))来利用信号的稀疏性,以减少获取的数据量和能耗。作为天体信号的一个例子,我们分析了40MHz带宽内的真实木星信号。我们已经证明其最佳稀疏度是在频域中,稀疏度至少为10%,并且通过文献综述,我们选择了非均匀采样器(NUS)作为接收器体系结构。实施了一种评估木星信号重建的方法,以评估CS压缩对相关信号的影响。

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