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Comparison between the Kalman and the Non-Linear Least-Squares Estimators in Low Signal-to-Noise Ratio Lidar Inversion
2008
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium
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 leastsquares (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,
doi:10.1109/igarss.2008.4779542
dblp:conf/igarss/RocadenboschSCR08
fatcat:jvrqnurcpbewtkzc6le67q7nnq