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Research on RFID Virtual Tag Location Algorithm Based on Monte Carlo

机译:基于Monte Carlo的RFID虚拟标签位置算法研究

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Aiming at the problems of large positioning error and low positioning effect at the boundary of traditional RFID virtual tag positioning algorithm, this paper compares the influence of four different interpolation methods of virtual reference tag signal strength on positioning accuracy, and proposes a RFID virtual tag positioning algorithm based on Monte Carlo. The algorithm uses dynamic particles to replace the traditional static reference tag; introduces particle swarm optimization algorithm to update the Monte Carlo sample particle swarm, and gives different weights to the sampling particles based on the signal strength difference between the sampling particles and the undetermined tags, and finally completes the localization of the unknown tags through Monte Carlo resampling. The simulation results show that the algorithm can effectively improve the accuracy and stability of RFID positioning system compared with the traditional virtual tag positioning algorithm.
机译:针对传统RFID虚拟标签定位算法边界的大定位误差和低定位效应的问题,比较了四种不同插值方法对定位精度的四种不同插值方法的影响,并提出了RFID虚拟标签定位基于Monte Carlo的算法。该算法使用动态粒子来取代传统的静态参考标签;介绍粒子群优化算法以更新蒙特卡罗样本粒子群,并基于采样粒子和未确定标签之间的信号强度差给采样粒子给出不同的权重,最终通过蒙特卡罗重新采样完成未知标签的本地化。仿真结果表明,与传统的虚拟标签定位算法相比,该算法可以有效提高RFID定位系统的准确性和稳定性。

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