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Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing

In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along...

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Detalles Bibliográficos
Autores principales: Jiao, Zhongke, Liu, Bo, Liu, Enhai, Yue, Yongjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634513/
https://www.ncbi.nlm.nih.gov/pubmed/26473881
http://dx.doi.org/10.3390/s151026085
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author Jiao, Zhongke
Liu, Bo
Liu, Enhai
Yue, Yongjian
author_facet Jiao, Zhongke
Liu, Bo
Liu, Enhai
Yue, Yongjian
author_sort Jiao, Zhongke
collection PubMed
description In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL). Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing.
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spelling pubmed-46345132015-11-23 Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing Jiao, Zhongke Liu, Bo Liu, Enhai Yue, Yongjian Sensors (Basel) Article In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL). Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing. MDPI 2015-10-14 /pmc/articles/PMC4634513/ /pubmed/26473881 http://dx.doi.org/10.3390/s151026085 Text en © 2015 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 license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jiao, Zhongke
Liu, Bo
Liu, Enhai
Yue, Yongjian
Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing
title Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing
title_full Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing
title_fullStr Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing
title_full_unstemmed Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing
title_short Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing
title_sort low-pass parabolic fft filter for airborne and satellite lidar signal processing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634513/
https://www.ncbi.nlm.nih.gov/pubmed/26473881
http://dx.doi.org/10.3390/s151026085
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