Performance of Discrete-Fourier-Transform-Based Velocity Estimators for a Wind-Sensing Coherent Doppler Lidar System in the Kolmogorov Turbulence Regime

The performance of discrete-Fourier-transform (DFT)-based velocity estimators for wind-sensing coherent Doppler lidar systems in the Kolmogorov turbulence regime is summarized using Monte Carlo simulations. Furthermore, a signal model, a simulation procedure, velocity estimators, and simulation conditions are explained. The relationships between signal-to-noise ratio, line-of-sight velocity estimation precision, and signal detection probability are simulated and summarized. In addition to the basic DFT estimator, signal matching estimators which utilize DFT are studied. The performances in the Kolmogorov turbulence regime and those in the Gaussian autocovariance signal model are compared. The performances are compared for wavelength regions of 1.5, 2, and 10 mum.

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