Adaptive Visible Light Positioning with MSE Inner Loop for Underwater Environment

A. Vegni, V. Loscrí
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引用次数: 2

Abstract

The Internet of Underwater Things is a paradigm coming up beside well-known Internet of Things, but focusing on a specific environment that is the underwater scenario. Due to high attenuation and then limited performance, communication links in this harsh scenario are provided by dedicated wireless technologies such as optical wireless communication, acoustic communication. The high data rate achievable with underwater optical wireless makes it an enabling candidate technology for effective underwater communication systems. One of the most prominent topics related with underwater communication, is localisation, for all those underwater applications requiring high accuracy, such as marine ecology, seabed monitoring, etc. However, the high dynamic characteristics of the underwater environment can limit the localisation accuracy, thus resulting in high estimation errors. In this paper, we present an adaptive localisation algorithm that exploits optical wireless connectivity, in the visible range. It takes into account information about water turbidity and is able to dynamically correct the estimation error in case of variable water conditions. The effectiveness of the proposed approach has been compared to a previous technique, which does not exploit information about the environment and then results to be effective only if exists an apriori knowledge of the real water conditions.
基于MSE内环的水下环境自适应可见光定位
水下物联网是继众所周知的物联网之后的一个范例,但侧重于水下场景的特定环境。由于高衰减和有限的性能,在这种恶劣的场景下,通信链路是由专用的无线技术提供的,如光无线通信、声通信。水下光无线通信的高数据速率使其成为有效的水下通信系统的候选技术。与水下通信相关的最突出的主题之一是定位,用于所有需要高精度的水下应用,如海洋生态学,海底监测等。然而,水下环境的高动态特性会限制定位精度,从而导致较高的估计误差。在本文中,我们提出了一种在可见范围内利用光学无线连接的自适应定位算法。它考虑了水的浊度信息,并能在不同的水条件下动态修正估计误差。所提出的方法的有效性已与以前的技术进行了比较,后者不利用有关环境的信息,然后只有在存在真实水条件的先验知识的情况下才有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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