Enhanced dual filter for floating wind lidar motion correction: The impact of wind and initial scan phase models
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Cita com:
hdl:2117/374145
Tipus de documentArticle
Data publicació2022-09-21
EditorMultidisciplinary Digital Publishing Institute (MDPI)
Condicions d'accésAccés obert
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Reconeixement 4.0 Internacional
ProjecteTELEDETECCION ATMOSFERICA MEDIANTE SENSORES COOPERATIVOS LIDAR, RADAR Y PASIVOS: APLICACIONES SOBRE TIERRA Y MAR PARA LA OBSERVACION ATMOSFERICA Y ENERGIA EOLICA OFF-SHORE (AEI-PGC2018-094132-B-I00)
ACTRIS IMP - Aerosol, Clouds and Trace Gases Research Infrastructure Implementation Project (EC-H2020-871115)
ATMO-ACCESS - Solutions for Sustainable Access to Atmospheric Research Facilities (EC-H2020-101008004)
ACTRIS IMP - Aerosol, Clouds and Trace Gases Research Infrastructure Implementation Project (EC-H2020-871115)
ATMO-ACCESS - Solutions for Sustainable Access to Atmospheric Research Facilities (EC-H2020-101008004)
Abstract
An enhanced filter for floating Doppler wind lidar motion correction is presented. The filter relies on an unscented Kalman filter prototype for floating-lidar motion correction without access to the internal line-of-sight measurements of the lidar. In the present work, we implement a new architecture based on two cooperative estimation filters and study the impact of different wind and initial scan phase models on the filter performance in the coastal environment of Barcelona. Two model combinations are considered: (i) a basic random walk model for both the wind turbulence and the initial scan phase and (ii) an auto-regressive model for wind turbulence along with a uniform circular motion model for the scan phase. The filter motion-correction performance using each of the above models was evaluated with reference to a fixed lidar in different wind and motion scenarios (low- and high-frequency turbulence cases) recorded during a 25-day campaign at “Pont del Petroli”, Barcelona, by clustered statistical analysis. The auto-regressive wind model and the uniform circular motion phase model permitted the filter to overcome divergence in all wind and motion scenarios. The statistical indicators comparing both instruments showed overall improvement. The mean deviation increased from 1.62% (without motion correction) to -0.07% (with motion correction), while the root-mean-square error decreased from 1.87% to 0.58%, and the determination coefficient (R2) improved from 0.90 to 0.96.
CitacióSalcedo, A.; Rocadenbosch, F.; Sospedra, J. Enhanced dual filter for floating wind lidar motion correction: The impact of wind and initial scan phase models. "Remote sensing", 21 Setembre 2022, vol. 14, núm. 19, article 4704, p. 1-23.
ISSN2072-4292
Versió de l'editorhttps://www.mdpi.com/2072-4292/14/19/4704/htm
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