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8 December 2022 Period estimation of noise-laden signals under non-integer period truncation
Chunyan Liu, Liangyu Chen, Xin Li, Pinjia Zeng, Jiaojiao Bai, Shen Fan
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Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124742F (2022) https://doi.org/10.1117/12.2653457
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China
Abstract
In the field of digital signal analysis and processing, discrete spectrum analysis is always an inevitable research topic. Signal period estimation plays an important role in improving the accuracy of spectrum analysis. When we perform truncation analysis on the signal, it is inevitable that the signal will be truncated by non-integral period, resulting in spectrum leakage. In this paper, we study the spectrum leakage law, obtain the leakage law of spectrum leakage attenuating by Gaussian function approximately along the frequency direction, and propose the minimum energy leakage period estimation method based on autocorrelation. The experimental results show that the algorithm is simple and can estimate the period of the signal when the signal-to-noise ratio is -10dB, which has strong anti-noise characteristics.
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Chunyan Liu, Liangyu Chen, Xin Li, Pinjia Zeng, Jiaojiao Bai, and Shen Fan "Period estimation of noise-laden signals under non-integer period truncation", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124742F (8 December 2022); https://doi.org/10.1117/12.2653457
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KEYWORDS
Signal to noise ratio
Spectrum analysis
Digital signal processing
Error analysis
Fourier transforms
Analytical research
Electronic filtering
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