Inversion probability enhancement of allfiber CDWL by noise modeling and robust fitting
Abstract
Accurate power spectrum analysis of weak backscattered signals are the primary constraint in longdistance coherent Doppler wind lidar (CDWL) applications. To study the atmospheric boundary layer, an allfiber CDWL with 300µJ pulse energy is developed. In principle, the coherent detection method can approach the quantum limit sensitivity if the noise in the photodetector output is dominated by the shot noise of the local oscillator. In practice, however, abnormal power spectra occur randomly, resulting in error estimation and low inversion probability. This phenomenon is theoretically analyzed and shown to be due to the leakage of a timevarying DC noise of the balanced detector. Thus, a correction algorithm with accurate noise modeling is proposed and demonstrated. The accuracy of radial velocity, carriertonoise ratio (CNR), and spectral width are improved. In wind profiling process, a robust sinewave fitting algorithm with data quality control is adopted in the velocityazimuth display (VAD) scanning detection. Finally, in 5day continuous wind detection, the inversion probability is tremendously enhanced. As an example, it is increased from 8.6% to 52.1% at the height of 4 km.
 Publication:

Optics Express
 Pub Date:
 September 2020
 DOI:
 10.1364/OE.401054
 Bibcode:
 2020OExpr..2829662W