Adaptive iteratively reweighted sine wave fitting method for rapid wind vector estimation of pulsed coherent Doppler lidar

Wind vector estimation method that provides more available data in low signal-to-noise ratio (SNR) regime improves the performance of pulsed coherent Doppler lidar. The adaptive iteratively reweighted sine wave fitting (airSWF) method proposed here reweights the contribution of each radial wind velocity adaptively and iteratively when estimating the wind vector. Based on the processing results of both the simulated and real-captured signal, the airSWF method provides more available wind vector estimates with little computational time increment, compared with the direct sine wave fitting (DSWF) and weighted DSWF methods. Specifically, the proportion of available wind vector estimates determined using the airSWF method increases by >20% when the detection height exceeds 1 km. Another significant advantage of the airSWF method over the filtered sine wave fitting (FSWF) method is that no prior knowledge is required. Moreover, the computational complexity of the airSWF method is lower than that of the FSWF and maximum of the function of accumulated spectra methods.