Fig. 1

Deep neural network method for underwater geolocalization based on celestial-based underwater polarization information in low and high visibility waters by day and by night. a–c We deployed an underwater polarization sensitive imaging system with an omnidirectional lens in high and low visibility waters to collect the required data. False-color images of the measured angle of polarization (AoP) and a graph comparing observed AoP with the parametric model’s prediction are displayed next to each drawing. Predictions made by the parametric model are unreliable in low visibility waters and it is ineffective at night. d We selected four different sites as indicated on the global map to collect underwater data and to assess the effectiveness of our geolocalization method. e Our deep neural network, in conjunction with a particle filter, uses sequences of AoP images to estimate the camera’s position latitude and longitude