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A Hardware Implemented Autocorrelation Technique for Estimating Power Spectral Density for Processing Signals from a Doppler Wind Lidar System

A signal processing technique utilizing autocorrelation of backscattered signals was designed and implemented in a 1.5 µm all-fiber wind sensing Coherent Doppler Lidar (CDL) system to preprocess atmospheric signals. The signal processing algorithm’s design and implementation are presented. The syste...

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Detalles Bibliográficos
Autores principales: Abdelazim, Sameh, Santoro, David, Arend, Mark, Moshary, Fred, Ahmed, Sam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308451/
https://www.ncbi.nlm.nih.gov/pubmed/30486511
http://dx.doi.org/10.3390/s18124170
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author Abdelazim, Sameh
Santoro, David
Arend, Mark
Moshary, Fred
Ahmed, Sam
author_facet Abdelazim, Sameh
Santoro, David
Arend, Mark
Moshary, Fred
Ahmed, Sam
author_sort Abdelazim, Sameh
collection PubMed
description A signal processing technique utilizing autocorrelation of backscattered signals was designed and implemented in a 1.5 µm all-fiber wind sensing Coherent Doppler Lidar (CDL) system to preprocess atmospheric signals. The signal processing algorithm’s design and implementation are presented. The system employs a 20 kHz pulse repetition frequency (PRF) transmitter and samples the return signals at 400 MHz. The logic design of the autocorrelation algorithm was developed and programmed into a field programmable gate array (FPGA) located on a data acquisition board. The design generates and accumulates real time correlograms representing average autocorrelations of the Doppler shifted echo from a series of adjustable range gates. Accumulated correlograms are streamed to a host computer for subsequent processing to yield a line of sight wind velocity. Wind velocity estimates can be obtained under nominal aerosol loading and nominal atmospheric turbulence conditions for ranges up to 3 km.
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spelling pubmed-63084512019-01-04 A Hardware Implemented Autocorrelation Technique for Estimating Power Spectral Density for Processing Signals from a Doppler Wind Lidar System Abdelazim, Sameh Santoro, David Arend, Mark Moshary, Fred Ahmed, Sam Sensors (Basel) Article A signal processing technique utilizing autocorrelation of backscattered signals was designed and implemented in a 1.5 µm all-fiber wind sensing Coherent Doppler Lidar (CDL) system to preprocess atmospheric signals. The signal processing algorithm’s design and implementation are presented. The system employs a 20 kHz pulse repetition frequency (PRF) transmitter and samples the return signals at 400 MHz. The logic design of the autocorrelation algorithm was developed and programmed into a field programmable gate array (FPGA) located on a data acquisition board. The design generates and accumulates real time correlograms representing average autocorrelations of the Doppler shifted echo from a series of adjustable range gates. Accumulated correlograms are streamed to a host computer for subsequent processing to yield a line of sight wind velocity. Wind velocity estimates can be obtained under nominal aerosol loading and nominal atmospheric turbulence conditions for ranges up to 3 km. MDPI 2018-11-28 /pmc/articles/PMC6308451/ /pubmed/30486511 http://dx.doi.org/10.3390/s18124170 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Abdelazim, Sameh
Santoro, David
Arend, Mark
Moshary, Fred
Ahmed, Sam
A Hardware Implemented Autocorrelation Technique for Estimating Power Spectral Density for Processing Signals from a Doppler Wind Lidar System
title A Hardware Implemented Autocorrelation Technique for Estimating Power Spectral Density for Processing Signals from a Doppler Wind Lidar System
title_full A Hardware Implemented Autocorrelation Technique for Estimating Power Spectral Density for Processing Signals from a Doppler Wind Lidar System
title_fullStr A Hardware Implemented Autocorrelation Technique for Estimating Power Spectral Density for Processing Signals from a Doppler Wind Lidar System
title_full_unstemmed A Hardware Implemented Autocorrelation Technique for Estimating Power Spectral Density for Processing Signals from a Doppler Wind Lidar System
title_short A Hardware Implemented Autocorrelation Technique for Estimating Power Spectral Density for Processing Signals from a Doppler Wind Lidar System
title_sort hardware implemented autocorrelation technique for estimating power spectral density for processing signals from a doppler wind lidar system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308451/
https://www.ncbi.nlm.nih.gov/pubmed/30486511
http://dx.doi.org/10.3390/s18124170
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