Abstract
The performance of mean velocity estimators is determined by
computer simulations for solid-state coherent Doppler lidar
measurements of wind fields at a cloud interface with deterministic
profiles of velocity and aerosol backscatter. Performance of the
velocity estimates is characterized by the standard deviation about the
estimated mean and the bias referenced to the input velocity. A new
class of estimators are required for cloud conditions, as traditional
techniques result in biased estimates. We consider data with high
signal energy that produces negligible random outliers.
© 1998 Optical Society of America
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