Extended Kalman Filter-Based Active Alignment Control for LED Optical Communication

Extended Kalman Filter-Based Active Alignment Control for LED Optical Communication
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DOI:
10.1109/tmech.2018.2841643
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发表时间:
2018-05
期刊:
IEEE/ASME Transactions on Mechatronics
影响因子:
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通讯作者:
P. Solanki;Mohammed Al-Rubaiai;Xiaobo Tan
P. Solanki;Mohammed Al-Rubaiai;Xiaobo Tan
中科院分区:
其他
文献类型:
--
作者:
P. Solanki;Mohammed Al-Rubaiai;Xiaobo Tan

文献摘要

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基于发光二极管(LED)的光通信作为一种低功耗、低成本、高数据速率的水下移动声频通信替代品正在兴起。然而,它要求发射器和接收器之间有一个近视距(LOS)链路。由于推进和不必要的干扰导致底层移动平台不断移动,因此保持LOS的对齐具有挑战性。在本文中,我们提出了一种新颖的,紧凑的基于led的通信系统,该系统具有主动对准控制,在二维设置中,尽管底层平台移动,但仍能保持LOS。提出了一种基于扩展卡尔曼滤波的估计接收机方向与收发线夹角的算法,并利用该算法对接收机方向进行调整。该算法仅使用来自单个光电二极管的测量光强度,其中通过扫描技术获得连续测量。设计了一个简单的比例控制器用于对准,同时也保证了系统的可观察性。仿真和实验验证了主动对准算法的有效性。特别是,通过与基于爬坡和三点平均的两种替代算法的比较,证明了其在测量噪声存在下的鲁棒性。
Light-emitting diode (LED)-based optical communication is emerging as a low-power, low-cost, and high-data rate alternative to acoustic communication for mobile applications underwater. However, it requires a close-to- line-of-sight (LOS) link between the transmitter and the receiver. Alignment for maintaining LOS is challenging due to the constant movement of underlying mobile platforms caused by propulsion and unwanted disturbances. In this paper, we present a novel, compact LED-based communication system with active alignment control, in a two-dimensional setting, that maintains the LOS despite the underlying platform movement. An extended Kalman filter-based algorithm is proposed to estimate the angle between the receiver orientation and the receiver–transmitter line, which is used subsequently to adjust the receiver orientation. The algorithm uses only the measured light intensity from a single photodiode, where successive measurements are obtained via a scanning technique. A simple proportional controller is designed for alignment that also ensures the observability of the system. The effectiveness of the proposed active alignment algorithm is verified in simulation and experiments. In particular, its robustness in the presence of measurement noise is demonstrated via comparison with two alternative algorithms that are based on hill-climbing and three-point-averaging.