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Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization

机译:能量收集混合声光水下无线传感器网络的本地化

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摘要

Underwater Wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, more power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate for limited communication distance. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node.udThe ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. In this paper, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (EH-AO-UWSNs) is proposed. EH-AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in EH-AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.
机译:水下无线技术要求以更高的数据速率传输以进行海洋勘探。当前,声传感器网络以低数据速率,高成本,高等待时间,更多功耗以及对海洋哺乳动物的负面影响实现了大范围的覆盖。同时,用于水下网络的光通信具有在有限的通信距离下具有较高数据速率的优点。此外,由于电池电量有限以及难以更换或为传感器节点的电池充电,因此能耗是水下传感器网络的另一个主要问题。 ud此问题的最终解决方案是为声光传感器增加能量收集功能节点。在本文中,提出了一种新的能量收集混合声光水下无线传感器网络(EH-AO-UWSNs)的定位技术。 EH-AO-UWSN在较短的传输距离上采用光通信以提高数据速率,而在较低的数据速率和长传输距离下采用声波通信。提出了一种基于混合接收信号强度(RSS)的定位技术来定位EH-AO-UWSN中的节点。所提出的技术结合了来自声通信和光通信的基于噪声的RSS测量,并估计了声光传感器节点的最终位置。针对混合估计距离,提出了加权多重观测范式,以抑制噪声观测,并更加重视精确观测。此外,针对所提出技术的定位精度,导出了Cramer-Rao下界(CRLB)的闭式解。

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