U-star
Xiao Zhang, Hanqing Guo, James Mariani, Li Xiao
Abstract
Underwater optical wireless communication techniques are promising due to a broad bandwidth with a long communication range compared with existing expensive acoustic and RF-based underwater communication techniques. For underwater navigation assistance during dive and rescue, it is more practical to adopt passive optical tags for objects/human identification and location-based services. However, existing optical tags (bar/QR codes) employ one/two dimensional designs, which lack significant element/symbol distance for robust decoding and full-directional localization capabilities for underwater navigation tasks. This paper investigates opportunities to increase the element distance in passive low-order optical tags by exploiting 3D spatial diversity. Specifically, we design U-Star, a system that consists of Underwater Optical Identification (UOID) tags and commercial camera-based tag readers for underwater navigation. Our UOID tags embed rich location and guidance information. Additionally, because our UOID tags employ a three-dimensional design, they can also determine the relative location of a user in real-time based on the perspective principles. We design AI based mobile algorithms for underwater denoising, relative positioning, and robust data parsing for tag readers. Finally, we evaluate U-Star on real UOID tag prototypes under different underwater scenarios. Results show that our 3-order UOID tag can embed 21 bits with a BER of 0.003 at 1m and less than 0.05 at up to 3m, which is sufficient for underwater navigation guidance with backup database.