Evaluation of coherent Doppler lidar velocity estimators in nonstationary regimes

High-resolution Doppler-velocity estimation techniques for processing of coherent heterodyne pulsed lidar data

On the basis of an analysis of the autocovariance of the complex heterodyne signal, some novel algorithms are derived and are investigated for use in determining, with high spatial resolution, Doppler-velocity coherent-lidar profiles in the case of rectangular and rectangularlike sensing laser pulses. These algorithms generalize other known Doppler-velocity estimators for the more complex case of nonuniform scattering and Doppler-velocity distribution within the pulse length. Algorithm performance and efficiency are studied and are illustrated by computer simulations. It is shown that the Doppler-velocity profiles can be determined with essentially better resolution in comparison with the use of other known estimation approaches, but at the expense of some increase in the number of statistical realizations (number of laser shots) required to reduce the speckle-noise effect. The minimum achievable resolution interval is shown to be much shorter than the pulse length.

Coherent Doppler lidar signal spectrum with wind turbulence

The average signal spectrum (periodogram) for coherent Doppler lidar is calculated for a turbulent wind field. Simple approximations are compared with the exact calculation. The effects of random errors in the zero velocity reference, the effects of averaging spectral estimates by use of multiple lidar pulses, and the effects of the range dependence of the lidar signal power over the range gate are included. For high spatial resolution measurements the lidar signal power is concentrated around one spectral estimate (spectral bin), and correct interpretation of the contribution from turbulence is difficult because of the effects of spectral leakage. For range gates that are larger than the lidar pulse volume, the signal power is contained in many spectral bins and the effects of turbulence can be determined accurately for constant signal power over the range gate and for the far-field range dependence of the signal power.

Extracting vertical winds from simulated clouds with ground-based coherent Doppler lidar

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.