Simulated Sinewave Testing of DataAcquisition Systems using SineFitting and Discrete Fourier Transform Methods Part 1: Frequency Offset, Random, Quantization, and Jitter Noise

Published

July 30, 2015

Author(s)

Jon C. Geist, Muhammad Y. Afridi

Abstract

This report studies the effect of frequency offset, quantization error, random additive noise, and random phase jitter on the results of sine fitting and performing Discreet Fourier Transforms (DFT) of measurements of sinewaves with Data Acquisition Systems (DAS). Quantization error is the only effect of non-linearity that is considered. The majority of the simulations are carried out for full-scale signals on a 16-bit DAS, but the simulations do not simulate the effect of clipping on portions of noisy signals that require more than 16 bits. Instead, the signals are rounded in way that provides the minimum number of bits required to represent the integer part of the signal. The results of this approach are easier to interpret and simple corrections for this shortcoming are given. Among other results, it is shown that probability plots of the residuals of fits of sinewave fits to measured sinewaves can distinguish among random additive noise, random jitter, and frequency offset error when the effect of quantization noise is small compared to the effects of these other sources of distortion.

Citation

NIST Interagency/Internal Report (NISTIR) -

NIST Pub Series

NIST Interagency/Internal Report (NISTIR)

Pub Type

NIST Pubs

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DOI Link

Keywords

DAS, data acquisition system, DFT, discrete Fourier transform, frequency error, jitter, noise, quantization, sinewave, sine test

Citation

Geist, J. and Afridi, M. (2015), Simulated Sinewave Testing of DataAcquisition Systems using SineFitting and Discrete Fourier Transform Methods Part 1: Frequency Offset, Random, Quantization, and Jitter Noise, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.IR.8073 (Accessed October 11, 2024)