Spectral analysis techniques using Prism signal processing. (February 2021)

• Record Type: Journal Article
• Authors: Henry, Manus
• Is Part Of: Measurement. Volume 169(2021)
• Publication Date: 2021-02
• Subjects: FFT -- Prism signal processing -- Spectral analysis -- Spectral leakage -- Hidden tones; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2020.108491
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Prism, a recursive FIR filtering technique, is applied to spectral analysis. The technique is effective at detecting and rejecting spectral leakage. Hidden tones located with accurate estimates of frequency, amplitude and phase. Simulation example: two adjacent spectral peaks with amplitudes 0.5 and 1e-9. For each peak, frequency, amplitude and phase are calculated accurately. 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.