Algorithms for Accurate Spectral Analysis in the Presence of Arbitrary Non-coherency and Large Distortion

  • Authors:
    Yuming Zhuang (Iowa St Univ.), Degang Chen (Iowa St Univ.)
    Publication ID:
    P090860
    Publication Type:
    Paper
    Received Date:
    8-May-2017
    Last Edit Date:
    8-May-2017
    Research:
    1836.127 (Iowa State University)

Abstract

In spectral analysis, achieving coherent sampling, especially when signals have large distortion, has been a challenge for many years. This paper introduces three algorithms to resolve this issue. In comparison to previous algorithms, and two widely used methods in industry: windowing and four parameter sine wave fit, these new algorithms are capable of obtaining accurate spectral results of the signal, while achieving high accuracy as well as computational efficiency. The novel contribution of this paper is that not only it proposed two new algorithms, but it also analyzed their advantages and limitations in detail, providing their trade-offs and different fields of applications. Extensive simulations and measurements are performed to validate these algorithms. Combined with their high accuracy, computational efficiency and robustness against signal purity, these algorithms are readily available to be implemented for bench or on-chip testing. In addition, it is suitable for data converter spectral testing when non-coherent sampling is present, and spectrally pure test signal source is not available.

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