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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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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. |
format | Online Article Text |
id | pubmed-4634513 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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