U-star: an underwater navigation system based on passive 3D optical identification tags

U-star: an underwater navigation system based on passive 3D optical identification tags
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DOI:
10.1145/3495243.3517019
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发表时间:
2022-10
期刊:
Proceedings of the 28th Annual International Conference on Mobile Computing And Networking
影响因子:
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通讯作者:
Xiao Zhang;Hanqing Guo;James Mariani;Li Xiao
Xiao Zhang;Hanqing Guo;James Mariani;Li Xiao
中科院分区:
其他
文献类型:
--
作者:
Xiao Zhang;Hanqing Guo;James Mariani;Li Xiao

文献摘要

相似文献

与现有的昂贵的声学和基于RF的水下通信技术相比,水下光无线通信技术由于具有宽的带宽和长的通信距离而具有很大的发展前景。对于潜水和救援期间的水下导航辅助,采用无源光学标签进行物体/人识别和基于位置的服务是更实用的。然而,现有的光学标签(条形码/QR码)采用一维/二维设计,缺乏显著的元素/符号距离的鲁棒解码和全方位定位能力的水下导航任务。本文研究了利用三维空间分集来增加无源低阶光学标签中的元件距离的机会。具体来说,我们设计了U-Star,这是一个由水下光学识别(UNOPS)标签和基于商业相机的标签阅读器组成的水下导航系统。我们的Uplink标签嵌入了丰富的位置和指南信息。此外,由于我们的Uplink标签采用三维设计,因此它们还可以根据透视原理实时确定用户的相对位置。我们设计了基于AI的移动的算法,用于水下去噪、相对定位和标签读取器的强大数据解析。最后,我们评估了U-Star在不同的水下场景下的真实的Umbuds标签原型。结果表明,我们的三阶UBER标签可以嵌入21位,误码率为0.003在1米和小于0.05在长达3米,这是足够的水下导航与备份数据库的引导。
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.