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Coherently averaged power spectral estimate for signal detection

Coherently averaged power spectral estimate for signal detection
Coherently averaged power spectral estimate for signal detection
A common approach to detect sinusoidal signals buried in noise is based on spectral analysis, such as the periodogram. The fluctuations of the spectral components associated with the noise can be alleviated via incoherent averaging of the power spectral estimates of each segment, which is the basis of Welch's method. However, Welch's method only utilizes the incoherent information between segments of signals. In this paper, we propose a method of coherent averaging between segments, which enhances ratio of time-invariant sinusoidal signals relative to the level of the noise background. The gain of coherent averaged power spectral estimate has been derived in terms of time duration of the signal. The proposed method provides a flexible, computationally efficient implementation of signal detection, which can be formulated to allow for various integration times to be realised in different frequency bands. Simulation and experimental results show that the proposed method outperforms the Welch's method and the periodogram method.
Signal detection, power spectral estimation, coherent averaging
0165-1684
1-10
Lan, Hualin
8cd1a21a-a6c3-4ca2-b0a1-a2b3ed2e9d50
White, Paul
2dd2477b-5aa9-42e2-9d19-0806d994eaba
Li, Na
f816fc15-5c6a-4c4c-82ed-c0dd1f5ae0a8
Li, Jianghui
9c589194-00fa-4d42-abaf-53a32789cc5e
Sun, Dajun
6956d99c-9898-4590-a459-71ea169de6d4
Lan, Hualin
8cd1a21a-a6c3-4ca2-b0a1-a2b3ed2e9d50
White, Paul
2dd2477b-5aa9-42e2-9d19-0806d994eaba
Li, Na
f816fc15-5c6a-4c4c-82ed-c0dd1f5ae0a8
Li, Jianghui
9c589194-00fa-4d42-abaf-53a32789cc5e
Sun, Dajun
6956d99c-9898-4590-a459-71ea169de6d4

Lan, Hualin, White, Paul, Li, Na, Li, Jianghui and Sun, Dajun (2020) Coherently averaged power spectral estimate for signal detection. Signal Processing, 169, 1-10, [107414]. (doi:10.1016/j.sigpro.2019.107414).

Record type: Article

Abstract

A common approach to detect sinusoidal signals buried in noise is based on spectral analysis, such as the periodogram. The fluctuations of the spectral components associated with the noise can be alleviated via incoherent averaging of the power spectral estimates of each segment, which is the basis of Welch's method. However, Welch's method only utilizes the incoherent information between segments of signals. In this paper, we propose a method of coherent averaging between segments, which enhances ratio of time-invariant sinusoidal signals relative to the level of the noise background. The gain of coherent averaged power spectral estimate has been derived in terms of time duration of the signal. The proposed method provides a flexible, computationally efficient implementation of signal detection, which can be formulated to allow for various integration times to be realised in different frequency bands. Simulation and experimental results show that the proposed method outperforms the Welch's method and the periodogram method.

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SIGPRO-D-19-00188 - Accepted Manuscript
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Accepted/In Press date: 1 December 2019
e-pub ahead of print date: 2 December 2019
Published date: April 2020
Keywords: Signal detection, power spectral estimation, coherent averaging

Identifiers

Local EPrints ID: 436562
URI: http://eprints.soton.ac.uk/id/eprint/436562
ISSN: 0165-1684
PURE UUID: 1c832cf9-47ff-4e17-9aee-9e1aac57727a
ORCID for Paul White: ORCID iD orcid.org/0000-0002-4787-8713
ORCID for Jianghui Li: ORCID iD orcid.org/0000-0002-2956-5940

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Date deposited: 13 Dec 2019 17:30
Last modified: 02 Dec 2020 05:01

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Contributors

Author: Hualin Lan
Author: Paul White ORCID iD
Author: Na Li
Author: Jianghui Li ORCID iD
Author: Dajun Sun

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