Spectral Analysis Techniques using Prism Signal Processing

Manus Henry

doi:10.1016/j.measurement.2020.108491

Spectral Analysis Techniques using Prism Signal Processing

Manus Henry

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

300 Downloads (Pure)

Abstract

The Prism is a new signal processing module which implements fully recursive, linear phase FIR filtering, so its computational cost is fixed irrespective of filter length. The Prism also has negligible design cost. Recent work has demonstrated how, using simple design rules, a chain of six Prisms can create a narrowband filter with arbitrary central frequency and bandwidth. In this paper, the technique is applied to spectral analysis of data, whereby a sequence of filters is applied to a data set to provide narrow frequency analysis, yielding accurate estimates of the frequencies and amplitudes of spectral peaks in the data. Although this time domain technique remains computationally expensive compared to the FFT, it can identify and reject spectral leakage, offering an alternative analysis for low amplitude and/or adjacent spectral peaks, including hidden tones, where FFT discrimination may be limited.

Original language	English
Article number	108491
Number of pages	11
Journal	Measurement
Volume	169
Early online date	28 Sept 2020
DOIs	https://doi.org/10.1016/j.measurement.2020.108491
Publication status	Published - Feb 2021

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Measurement. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Measurement, 169, (2021) DOI: 10.1016/j.measurement.2020.108491

© 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

FFT
Hidden tones
Prism signal processing
Spectral analysis
Spectral leakage

ASJC Scopus subject areas

Instrumentation
Electrical and Electronic Engineering

Access to Document

10.1016/j.measurement.2020.108491

Post-PrintAccepted author manuscript, 2.72 MBLicence: CC BY-NC-ND

Cite this

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title = "Spectral Analysis Techniques using Prism Signal Processing",

abstract = "The Prism is a new signal processing module which implements fully recursive, linear phase FIR filtering, so its computational cost is fixed irrespective of filter length. The Prism also has negligible design cost. Recent work has demonstrated how, using simple design rules, a chain of six Prisms can create a narrowband filter with arbitrary central frequency and bandwidth. In this paper, the technique is applied to spectral analysis of data, whereby a sequence of filters is applied to a data set to provide narrow frequency analysis, yielding accurate estimates of the frequencies and amplitudes of spectral peaks in the data. Although this time domain technique remains computationally expensive compared to the FFT, it can identify and reject spectral leakage, offering an alternative analysis for low amplitude and/or adjacent spectral peaks, including hidden tones, where FFT discrimination may be limited. ",

keywords = "FFT, Hidden tones, Prism signal processing, Spectral analysis, Spectral leakage",

author = "Manus Henry",

note = "NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in Measurement. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Measurement, 169, (2021) DOI: 10.1016/j.measurement.2020.108491 {\textcopyright} 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ ",

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N2 - The Prism is a new signal processing module which implements fully recursive, linear phase FIR filtering, so its computational cost is fixed irrespective of filter length. The Prism also has negligible design cost. Recent work has demonstrated how, using simple design rules, a chain of six Prisms can create a narrowband filter with arbitrary central frequency and bandwidth. In this paper, the technique is applied to spectral analysis of data, whereby a sequence of filters is applied to a data set to provide narrow frequency analysis, yielding accurate estimates of the frequencies and amplitudes of spectral peaks in the data. Although this time domain technique remains computationally expensive compared to the FFT, it can identify and reject spectral leakage, offering an alternative analysis for low amplitude and/or adjacent spectral peaks, including hidden tones, where FFT discrimination may be limited.

AB - The Prism is a new signal processing module which implements fully recursive, linear phase FIR filtering, so its computational cost is fixed irrespective of filter length. The Prism also has negligible design cost. Recent work has demonstrated how, using simple design rules, a chain of six Prisms can create a narrowband filter with arbitrary central frequency and bandwidth. In this paper, the technique is applied to spectral analysis of data, whereby a sequence of filters is applied to a data set to provide narrow frequency analysis, yielding accurate estimates of the frequencies and amplitudes of spectral peaks in the data. Although this time domain technique remains computationally expensive compared to the FFT, it can identify and reject spectral leakage, offering an alternative analysis for low amplitude and/or adjacent spectral peaks, including hidden tones, where FFT discrimination may be limited.

KW - FFT

KW - Hidden tones

KW - Prism signal processing

KW - Spectral analysis

KW - Spectral leakage

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VL - 169

JO - Measurement

JF - Measurement

M1 - 108491

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Spectral Analysis Techniques using Prism Signal Processing

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Manus Henry

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Spectral Analysis Techniques using Prism Signal Processing

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Manus Henry

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