Simultaneous sensing profiles of beam attenuation coefficient and volume scattering function at 180 using a single-photon underwater elastic-Raman lidar

Lidar has emerged as a promising technique for vertically profiling optical parameters in water. The application of single-photon technology has enabled the development of compact oceanic lidar systems, facilitating their deployment underwater. This is crucial for conducting ocean observations that are free from interference at the air-sea interface. However, simultaneous inversion of the volume scattering function at 180 degrees at 532 nm (beta m) and the lidar attenuation coefficient at 532 nm (Kmlidar) from the elastic backscattered signals remains challenging, especially in the case of near-field signals affected by the geometric overlap factor (GOF). To address this challenge, this work proposes adding a Raman channel, obtaining Raman backscattered profiles using single-photon detection. By normalizing the elastic backscattered signals with the Raman signals, the sensitivity of the normalized signal to variations in the lidar attenuation coefficient is significantly reduced. This allows for the application of a perturbation method to invert beta m and subsequently obtain the Kmlidar. Moreover, the influence of GOF and fluctuations in laser power on the inversion can be reduced. To further improve the accuracy of the inversion algorithm for stratified water bodies, an iterative algorithm is proposed. Additionally, since the optical telescope of the lidar adopts a small aperture and narrow field of view design, Kmlidar tends to the beam attenuation coefficient at 532 nm (cm). Using Monte Carlo simulation, a relationship between cm and Kmlidar is established, allowing cm derivation from Kmlidar. Finally, the feasibility of the algorithm is verified through inversion error analysis. The robustness of the lidar system and the effectiveness of the algorithm are validated through a preliminary experiment conducted in a water tank. These results demonstrate that the lidar can accurately profile optical parameters of water, contributing to the study of particulate organic carbon (POC) in the ocean.