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New Approach Based on Compressive Sampling for Sample Rate Enhancement in DASs for Low-Cost Sensing Nodes

机译:基于压缩采样的低成本传感节点DAS中增强采样率的新方法

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The paper deals with the problem of improving the maximum sample rate of analog-to-digital converters (ADCs) included in low cost wireless sensing nodes. To this aim, the authors propose an efficient acquisition strategy based on the combined use of high-resolution time-basis and compressive sampling. In particular, the high-resolution time-basis is adopted to provide a proper sequence of random sampling instants, and a suitable software procedure, based on compressive sampling approach, is exploited to reconstruct the signal of interest from the acquired samples. Thanks to the proposed strategy, the effective sample rate of the reconstructed signal can be as high as the frequency of the considered time-basis, thus significantly improving the inherent ADC sample rate. Several tests are carried out in simulated and real conditions to assess the performance of the proposed acquisition strategy in terms of reconstruction error. In particular, the results obtained in experimental tests with ADC included in actual 8- and 32-bits microcontrollers highlight the possibility of achieving effective sample rate up to 50 times higher than that of the original ADC sample rate.
机译:本文讨论了提高低成本无线传感节点中包含的模数转换器(ADC)的最大采样率的问题。为此,作者提出了一种基于高分辨率时基和压缩采样相结合的有效采集策略。特别地,采用高分辨率时基来提供适当的随机采样时刻序列,并且基于压缩采样方法,利用合适的软件过程从采集的样本中重建感兴趣的信号。由于所提出的策略,重构信号的有效采样率可以与所考虑的时基频率一样高,从而显着提高了固有ADC采样率。在模拟和真实条件下进行了几次测试,以根据重构误差评估所提出的采集策略的性能。特别是,在实际的8位和32位微控制器中包含ADC的实验测试中获得的结果突显了实现有效采样率的可能性,该有效采样率是原始ADC采样率的50倍。

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