Paper Info
Title
A Robust Adaptive Unscented Kalman Filter for Floating Doppler Wind-LiDAR Motion Correction
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.
Year
DOI
Venue
2021
10.3390/rs13204167
REMOTE SENSING
Keywords
DocType
Volume
floating Doppler Wind Lidar, apparent turbulence, motion compensation, adaptive filtering, Kalman Filter, Unscented Kalman Filter, six degrees of freedom
Journal
13
Issue
Citations 
PageRank 
20
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Andreu Salcedo-Bosch100.34
Francesc Rocadenbosch21714.54
Joaquim Sospedra300.68