Novel nonlinear adaptive Doppler-shift estimation technique for the coherent Doppler validation lidar

Abstract

The signal-processing aspect of a 2-µm wavelength-coherent Doppler lidar system under development at NASA Langley Research Center in Virginia is investigated in this paper. The system is named VALIDAR (validation lidar), and its signal-processing program estimates and displays various wind parameters in real time as data acquisition occurs. The goal is to improve the quality of the current estimates of power, Doppler shift, wind speed, and wind direction, especially in the low signal-to-noise-ratio (SNR) regime. A novel nonlinear adaptive Doppler-shift estimation technique (NADSET) is developed for this purpose, and its performance is analyzed using the wind data acquired over a long period of time by VALIDAR. The quality of Doppler-shift and power estimations by conventional Fourier-transform-based spectrum estimation methods deteriorates rapidly as the SNR decreases. NADSET compensates this deterioration by adaptively utilizing the statistics of Doppler-shift estimates in a strong SNR range and identifying sporadic range bins where good Doppler-shift estimates are found. The authenticity of NADSET is established by comparing the trend of wind parameters with and without NADSET applied to the long-period lidar return data.