Method of remotely sensing seawater salinity fine detection based on Raman Brillouin scattering

Abstract

Salinity is an important physical parameter in oceanography. The change of seawater salinity is closely related to the change of marine environment and climate. Investigation of seawater salinity is of great significance for marine biology, climate simulation, weather forecast and hurricane path prediction. At present, in the research of seawater salinity detection based on Raman scattering, the influence of temperature change is ignored, which will cause inaccurate detection results. In order to achieve high-precision detection of seawater salinity, in this paper, a method of combining the precision salinity inversion with ocean Brillouin scattering is proposed. According to the influence of temperature and salinity on Raman scattering spectra, the functional relationship between them is established. Raman scattering spectra and Brillouin frequency shift are used to implement the inversion seawater salinity. The Brillouin frequency shift cannot be obtained directly by the lidar remote sensing method. It can only detect the energy of the echo signal through edge detection, and the photon correlation spectroscopy technology is used to detect the spectra width. The Brillouin frequency shift can be calculated by the energy and spectral width of the echo signal. Therefore, the accurate inversion of seawater salinity can be realized by detecting Raman spectra, Brillouin spectra width and energy signal. The experimental results of Raman spectroscopy are used to verify the established functional relationship, and the inversion error of seawater salinity is less than 0.47‰. In the experiment, the influence of seawater temperature control accuracy of ±0.2 ℃ and the detection results of Brillouin spectrum width and energy are analyzed. Through using the error in measurement result of each parameter, the salinity inversion error caused by them is analyzed. Using the Raman spectrum and Brillouin frequency shift, the problem of the accurate inversion of seawater salinity is solved, and the influence of temperature change on salinity inversion is eliminated. This research provides reliable data support for improving the marine environment, early warning of marine disaster and marine meteorological forecast accuracy, and has important research value and significant social benefits. This method also provides a feasible solution for ocean detection lidar used to detect seawater salinity.