This paper presents a proof-of-concept optical detector array sensor system to be used in Unmanned Underwater Vehicle (UUV) navigation. The performance of the developed optical detector array was evaluated for its capability to estimate the position, orientation and forward velocity of UUVs with respect to a light source fixed in underwater. The evaluations were conducted through Monte Carlo simulations and empirical tests under a variety of motion configurations. Monte Carlo simulations also evaluated the system total propagated uncertainty (TPU) by taking into account variations in the water column turbidity, temperature and hardware noise that may degrade the system performance. Empirical tests were conducted to estimate UUV position and velocity during its navigation to a light beacon. Monte Carlo simulation and empirical results support the use of the detector array system for optics based position feedback for UUV positioning applications.
Airborne Lidar Bathymetry (ALB) provides a rapid means of data collection that provides seamless digital elevation maps across land and water. However, environmental factors such as water surface induce significant uncertainty in the ALB measurements. In this study, the effect of water surface on the ALB measurements is characterized both theoretically and empirically. Theoretical analysis includes Monte Carlo ray-tracing simulations that evaluate different environmental and hardware conditions such as wind speed, laser beam footprint diameter and off-nadir angle that are typically observed in ALB survey conditions. The empirical study includes development of an optical detector array to measure and analyze the refraction angle of the laser beam under a variety of environmental and hardware conditions. The results suggest that the refraction angle deviations ( ) in the along-wind direction vary between 3–5° when variations in wind speed, laser beam footprint size and the laser beam incidence angle are taken into account.
1 August 2019 in Photogrammetric Engineering & Remote Sensing