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Comparison between the Kalman and the non-linear least-squares estimators in low signal-to-noise ratio lidar inversion

Author
Rocadenbosch, F.; Sicard, M.; Comeron, A.; Md. Reba, M.
Type of activity
Presentation of work at congresses
Name of edition
2008 IEEE International Geoscience and Remote Sensing Symposium
Date of publication
2008
Presentation's date
2008-07
Book of congress proceedings
2008 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 6-11, 2008 John B. Hynes Veterans Memorial Convention Center
First page
1083
Last page
1086
DOI
https://doi.org/10.1109/IGARSS.2008.4779542 Open in new window
Repository
http://hdl.handle.net/2117/86960 Open in new window
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4779542 Open in new window
Abstract
This works departs from previously published results of the authors and focus on joint estimation and time evolution of the atmospheric backscatter profile and a range-independent lidar ratio by means of 1) adaptive extended Kalman filtering (EKF) and 2) non-linear least-squares (NLSQ), under moderate-to-low signal-to-noise ratios (SNR<100 at the starting sounding range). A Rayleigh/Mie atmosphere and a calibrated lidar system are considered. Performance parameters studied are data sufficiency, ...
Citation
Rocadenbosch, F., Sicard, M., Comeron, A., Md. Reba, M. Comparison between the Kalman and the non-linear least-squares estimators in low signal-to-noise ratio lidar inversion. A: IEEE International Geoscience and Remote Sensing Symposium. "2008 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 6-11, 2008 John B. Hynes Veterans Memorial Convention Center". 2008, p. 1083-1086.
Keywords
Inversion, Kalman filter, Least-squares, Lidar
Group of research
CommSensLab-UPC - Centre Específic de Recerca en Comunicació i Detecció UPC
RSLAB - Remote Sensing Lab

Participants