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Improving the visible light communication localization system using Kalman filtering with averaging

机译:使用kalman滤波改进可见光通信定位系统,平均

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摘要

Two techniques are proposed for improving the accuracy of localization estimation in indoor visible light communication systems, namely, averaging and Kalman filtering with averaging schemes. In the averaging technique, the receiver position is estimated using the received signal strength (RSS) indication method multiple times (e.g., N samples), and the acquired estimations are averaged over all samples. To further improve the localization, the Kalman filtering algorithm is adopted to estimate the received power over N samples, followed by applying the RSS technique on the average received power. The proposed techniques are analyzed mathematically, considering the effects of both line-of-sight (LOS) and first-reflection from non-LOS propagations. The performance of the proposed techniques is determined by evaluating the positioning errors in a typical room. The results are compared to that of the traditional RSS system. Simulation results reveal that an improvement of about 33.3% in the average positioning error is achievable when using the averaging scheme as compared to that of the traditional RSS scheme. This improvement increases to 72.2% when adopting the proposed Kalman filtering scheme. (C) 2020 Optical Society of America
机译:提出了两种提高室内可见光通信系统定位估计精度的方法,即平均法和卡尔曼滤波平均法。在平均技术中,使用接收信号强度(RSS)指示方法多次(例如,N个样本)估计接收器位置,并且在所有样本上平均获得的估计。为了进一步提高定位精度,采用卡尔曼滤波算法估计N个样本的接收功率,然后对平均接收功率应用RSS技术。对提出的技术进行了数学分析,同时考虑了视线(LOS)和非视线传播的首次反射的影响。所提出的技术的性能是通过评估典型房间中的定位误差来确定的。结果与传统RSS系统的结果进行了比较。仿真结果表明,与传统RSS方案相比,使用平均方案时,平均定位误差可提高约33.3%。当采用所提出的卡尔曼滤波方案时,这种改进增加到72.2%。(C) 2020美国光学学会

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