Coherent high-spectral-resolution lidar for the measurement of the atmospheric Mie–Rayleigh–Brillouin backscatter spectrum

Abstract

In this study, a 1550 nm coherent high-spectral-resolution lidar (CHSRL) is developed to measure the optical properties of aerosols and atmospheric wind profiles in the atmospheric boundary layer. To determine the optical properties, a coherent frequency discriminator based on the fast Fourier transform is designed in the CHSRL to separate the Mie and the Rayleigh–Brillouin backscatter spectra to fulfill the needs of high-spectral measurements. The atmospheric wind velocity is retrieved using the simultaneously measured Doppler shift. This non-optical frequency discriminator is a feasible and low-cost solution compared to a narrow-bandwidth optical filter, such as a Fabry–Perot interferometer or an atomic filter. However, shot, amplifier spontaneous emission, and detector noise interfere with the Rayleigh–Brillouin spectrum. Therefore, a spectrum correction algorithm is proposed to recover the interfered Rayleigh–Brillouin spectrum, and the measurement results of the spectral line agree well with those modeled with Tenti S6 at different central frequencies. Finally, field observations for comparison are conducted with the co-located CHSRL, Raman lidar, and coherent Doppler wind lidar. The comparison results indicate that the correlation coefficient of the aerosol backscatter coefficient is 0.84. The correlation coefficient and standard deviation of wind velocity are 0.98 and 0.13 m · s−1, respectively.

Field Verification of Vehicle-Mounted All-Fiber Coherent Wind Measurement Lidar Based on Four-Beam Vertical Azimuth Display Scanning

“…The wavelength of the laser has also changed from 10.6 µm [10] to 1.06 µm, and then to 2.0 µm [11] and 1.5 µm [12]. Recently, a 1.55 µm band all-fiber CWML has been widely used as the remote wind sensor for environmental wind field monitoring, owing to its advantages of high detection accuracy and strong anti-interference [13]. Windprofile Lidar mainly takes clear-air turbulence (CAT) as the detection object.…”

Enhanced Wind-Field Detection Using an Adaptive Noise-Reduction Peak-Retrieval (ANRPR) Algorithm for Coherent Doppler Lidar

“…It not only supports the development of weather forecasting [2] and climate modeling but also plays a significant role in monitoring air pollution [3], preventing weather disasters [4], and facilitating the development of renewable energy [5]. Coherent Doppler lidar (CDL), due to its advantages of high precision, large spatial coverage, and long detection range, is widely employed in atmospheric wind-field detection [4,6].…”