Approaches for Improved Doppler Estimation in Lidar Remote Sensing of Atmospheric Dynamics

Laser radar (Lidar) has been used extensively for remote sensing of wind patterns, turbulence in the atmospheric boundary layer and other important atmospheric transport phenomenon. As in most narrowband radar application, radial velocity of remote objects is encoded in the Doppler shift of the back...

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Main Authors: Bhaskaran Sreevatsan, Calhoun Ronald
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:EPJ Web of Conferences
Online Access:http://dx.doi.org/10.1051/epjconf/201611917015
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spelling doaj-a7262f9c88ab44aeadc1c118e63ffe242021-08-02T01:05:28ZengEDP SciencesEPJ Web of Conferences2100-014X2016-01-011191701510.1051/epjconf/201611917015epjconf_ilrc2016_17015Approaches for Improved Doppler Estimation in Lidar Remote Sensing of Atmospheric DynamicsBhaskaran SreevatsanCalhoun RonaldLaser radar (Lidar) has been used extensively for remote sensing of wind patterns, turbulence in the atmospheric boundary layer and other important atmospheric transport phenomenon. As in most narrowband radar application, radial velocity of remote objects is encoded in the Doppler shift of the backscattered signal relative to the transmitted signal. In contrast to many applications, however, the backscattered signal in atmospheric Lidar sensing arises from a multitude of moving particles in a spatial cell under examination rather than from a few prominent “target” scattering features. This complicates the process of extracting a single Doppler value and corresponding radial velocity figure to associate with the cell. This paper summarizes the prevalent methods for Doppler estimation in atmospheric Lidar applications and proposes a computationally efficient scheme for improving Doppler estimation by exploiting the local structure of spectral density estimates near spectral peaks.http://dx.doi.org/10.1051/epjconf/201611917015
collection DOAJ
language English
format Article
sources DOAJ
author Bhaskaran Sreevatsan
Calhoun Ronald
spellingShingle Bhaskaran Sreevatsan
Calhoun Ronald
Approaches for Improved Doppler Estimation in Lidar Remote Sensing of Atmospheric Dynamics
EPJ Web of Conferences
author_facet Bhaskaran Sreevatsan
Calhoun Ronald
author_sort Bhaskaran Sreevatsan
title Approaches for Improved Doppler Estimation in Lidar Remote Sensing of Atmospheric Dynamics
title_short Approaches for Improved Doppler Estimation in Lidar Remote Sensing of Atmospheric Dynamics
title_full Approaches for Improved Doppler Estimation in Lidar Remote Sensing of Atmospheric Dynamics
title_fullStr Approaches for Improved Doppler Estimation in Lidar Remote Sensing of Atmospheric Dynamics
title_full_unstemmed Approaches for Improved Doppler Estimation in Lidar Remote Sensing of Atmospheric Dynamics
title_sort approaches for improved doppler estimation in lidar remote sensing of atmospheric dynamics
publisher EDP Sciences
series EPJ Web of Conferences
issn 2100-014X
publishDate 2016-01-01
description Laser radar (Lidar) has been used extensively for remote sensing of wind patterns, turbulence in the atmospheric boundary layer and other important atmospheric transport phenomenon. As in most narrowband radar application, radial velocity of remote objects is encoded in the Doppler shift of the backscattered signal relative to the transmitted signal. In contrast to many applications, however, the backscattered signal in atmospheric Lidar sensing arises from a multitude of moving particles in a spatial cell under examination rather than from a few prominent “target” scattering features. This complicates the process of extracting a single Doppler value and corresponding radial velocity figure to associate with the cell. This paper summarizes the prevalent methods for Doppler estimation in atmospheric Lidar applications and proposes a computationally efficient scheme for improving Doppler estimation by exploiting the local structure of spectral density estimates near spectral peaks.
url http://dx.doi.org/10.1051/epjconf/201611917015
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AT calhounronald approachesforimproveddopplerestimationinlidarremotesensingofatmosphericdynamics
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