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Article

A Robust Adaptive Unscented Kalman Filter for Floating Doppler Wind-LiDAR Motion Correction

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CommSensLab-UPC, Unidad de Excelencia María de Maeztu, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya (UPC), E-08034 Barcelona, Spain
2
Institut d’Estudis Espacials de Catalunya (IEEC), Universitat Politècnica de Catalunya, E-08034 Barcelona, Spain
3
Laboratori d’Enginyeria Maritima, Universitat Politècnica de Catalunya, E-08034 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Hanwen Yu, Mi Wang, Jianlai Chen and Ying Zhu
Remote Sens. 2021, 13(20), 4167; https://doi.org/10.3390/rs13204167
Received: 2 September 2021 / Revised: 6 October 2021 / Accepted: 14 October 2021 / Published: 18 October 2021
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. View Full-Text
Keywords: floating Doppler Wind Lidar; apparent turbulence; motion compensation; adaptive filtering; Kalman Filter; Unscented Kalman Filter; six degrees of freedom floating Doppler Wind Lidar; apparent turbulence; motion compensation; adaptive filtering; Kalman Filter; Unscented Kalman Filter; six degrees of freedom
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MDPI and ACS Style

Salcedo-Bosch, A.; Rocadenbosch, F.; Sospedra, J. A Robust Adaptive Unscented Kalman Filter for Floating Doppler Wind-LiDAR Motion Correction. Remote Sens. 2021, 13, 4167. https://doi.org/10.3390/rs13204167

AMA Style

Salcedo-Bosch A, Rocadenbosch F, Sospedra J. A Robust Adaptive Unscented Kalman Filter for Floating Doppler Wind-LiDAR Motion Correction. Remote Sensing. 2021; 13(20):4167. https://doi.org/10.3390/rs13204167

Chicago/Turabian Style

Salcedo-Bosch, Andreu, Francesc Rocadenbosch, and Joaquim Sospedra. 2021. "A Robust Adaptive Unscented Kalman Filter for Floating Doppler Wind-LiDAR Motion Correction" Remote Sensing 13, no. 20: 4167. https://doi.org/10.3390/rs13204167

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