基于压缩采样的传感器网络频域测量节点

L. Angrisani, F. Bonavolontã, Alessandro Tocchi, R. S. L. Moriello
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引用次数: 16

摘要

研究了基于压缩采样(CS)的测量节点的设计与实现问题。所考虑的节点是为广域传感器网络量身定制的,旨在进行频域测量。为此,节点利用一些已知的或最近提出的CS特征,以优于其数据采集模块的标称规格。为了使频谱估计在节点级上可行,利用了一种合适的输入信号随机采样策略和一种有效的CS实现,即基于所谓匹配追踪方法的贪婪算法。首先对意法半导体的一款性价比高的微控制器进行了测试,即STM32F429ZI,其数据存储深度足以执行贪婪算法的敏捷计算方案。估计的光谱与基于离散傅里叶变换的标准方法得到的光谱一致,从而突出了所提出的测量节点的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Frequency domain measurement node based on compressive sampling for sensors networks
The paper deals with the problem of designing and implementing a measurement node based on compressive sampling (CS). The considered node is tailored for wide area sensors networks aimed to carry out measurements in frequency domain. To this aim, the node takes advantage from some known or recently proposed CS features in such a way as to outperform the nominal specification of its data acquisition module. To make the spectrum estimation feasible on the node level, a suitable strategy for input signal random sampling and an efficient CS implementation, i.e. the greedy algorithms based on the so-called match-pursuit approach, are exploited. First tests are presented, related to a cost-effective microcontroller from STMicrocontroller, namely STM32F429ZI, characterized by a data memory depth sufficient to execute the agile computational scheme of the greedy algorithm. The estimated spectra concur with those obtained through standard discrete Fourier transform-based approaches, thus highlighting the feasibility of the proposed measurement node.
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