Assessing the impact of optical vortex spatial filtering in underwater LiDAR systems

Blue-green underwater lidar has garnered significant interest due to its high spatial resolution and versatile deployment platforms. However, in turbid water, strong scattering limits both measurement range and ranging accuracy. By leveraging the spatial coherence difference between ballistic target reflections and scattered light, researchers have applied optical vortices as spatial filters to mitigate the scattering clutter in murky environments. Yet, in real underwater environments, turbulence and rough surfaces reduce the spatial coherence of target echo light, potentially diminishing the effectiveness of optical vortices in filtering out scattering noise. In this paper, we propose a multiple random phase screen model that accounts for scattering, turbulence, and target surface roughness to simulate laser beam transmission in water. We then use the improvement in the signal-to-clutter ratio and the transmittance of the spatial filter as criteria to analyze the effects of turbulence and surface roughness on the spatial filtering efficiency. Both the simulation and experimental results show that in contrast to analyzing an individual factor, the combined effect of turbulence and rough surfaces causes a greater decline in the spatial filter's effectiveness. When one factor is dominant and renders the spatial filter ineffective, the impact of the other factor on its performance is not evident. These findings offer valuable insights for designing spatial filtering in varied application scenarios.