A Robust Adaptive Unscented Kalman Filter for floating Doppler Wind-LiDAR motion correction
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Cita com:
hdl:2117/355110
Tipus de documentArticle
Data publicació2021-10-18
EditorMultidisciplinary Digital Publishing Institute (MDPI)
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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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
This study presents a new method for correcting the six degrees of freedom motion-induced error in ZephIR 300 floating Doppler Wind-LiDAR-derived data, based on a Robust Adaptive Unscented Kalman Filter. The filter takes advantage of the known floating Doppler Wind-LiDAR (FDWL) dynamics, a velocity–azimuth display algorithm, and a wind model describing the LiDAR-retrieved wind vector without motion influence. The filter estimates the corrected wind vector by adapting itself to different atmospheric and motion scenarios, and by estimating the covariance matrices of related noise processes. The measured turbulence intensity by the FDWL (with and without correction) was compared against a reference fixed LiDAR over a 25-day period at “El Pont del Petroli”, Barcelona. After correction, the apparent motion-induced turbulence was greatly reduced, and the statistical indicators showed overall improvement. Thus, the Mean Difference improved from -1.70% (uncorrected) to 0.36% (corrected), the Root Mean Square Error (RMSE) improved from 2.01% to 0.86%, and coefficient of determination improved from 0.85 to 0.93.
CitacióSalcedo, A.; Rocadenbosch, F.; Sospedra, J. A Robust Adaptive Unscented Kalman Filter for floating Doppler Wind-LiDAR motion correction. "Remote sensing", 18 Octubre 2021, vol. 13, núm. 20, article 4167, p. 1-23.
ISSN2072-4292
Versió de l'editorhttps://www.mdpi.com/2072-4292/13/20/4167
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