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An Improved Indoor UHF RFID Localization Method Based on Deviation Correction

机译:一种基于偏差校正的改进的室内UHF RFID定位方法

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In indoor localization environment, RFID signal propagation is complicated because of the reflection and diffraction and NLOS. The LANDMARC system and KNN algorithm cannot achieve satisfactory accuracy. By using the passive UHF RFID system, we propose an improved KNN method to rectify the target's coordinate position. First we use the traditional method to collect the reference tags RSSI and KNN algorithm to get the target position. Focused on the target's k nearest reference neighbor tags, we used the KNN algorithm k times to get each reference tag's calculated coordinate position. Compared with the known position, the average position deviation is used to get the target a more accuracy position. The simulation results dedicate that the improved KNN method increases localization accuracy and is suitable for the multi-targets indoor environment.
机译:在室内定位环境中,RFID信号的传播由于反射和衍射以及NLOS而变得很复杂。 LANDMARC系统和KNN算法无法达到令人满意的精度。通过使用无源UHF RFID系统,我们提出了一种改进的KNN方法来校正目标的坐标位置。首先,我们使用传统方法收集参考标签RSSI和KNN算法,以获取目标位置。针对目标的k个最近的参考邻居标签,我们使用了K次KNN算法来获取每个参考标签的计算坐标位置。与已知位置相比,平均位置偏差用于使目标获得更准确的位置。仿真结果表明,改进的KNN方法提高了定位精度,适用于多目标室内环境。

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