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Optimization of Indoor Positioning Algorithm Based on LANDMARC

机译:基于Landmarc的室内定位算法优化

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With the development of science and technology, RFID based indoor positioning technology is more and more widely used, among which LANDMARC indoor positioning system nearest neighbor algorithm has become the mainstream algorithm, aiming at the classic land The existence of multipath effect, noise random variable and various kinds of obstacles in the VIRE, Marc and its improved algorithm, makes reader reading ability decrease, affects the selection of nearest label, and then makes the positioning accuracy of the system decrease. This paper presents a new improvement scheme. Firstly, the RSSI is preprocessed by Gaussian filter, then the adaptive threshold is set, and the RSSI value of virtual reference label is obtained by Newton interpolation method. Then the positioning results are corrected by position correction. At the same time, the boundary virtual reference label is set, and the accuracy of RSSI is improved by these methods, and the coverage of reference label is increased. The simulation results show that the improved algorithm has higher positioning accuracy and stronger stability than LANDMARC and VIRE algorithm.
机译:随着科学技术的发展,基于RFID的室内定位技术是越来越广泛的使用,其中LANDMARC室内定位系统最近的邻居算法已成为主流算法,旨在经典的土地存在多径效应,噪声随机变量和噪声随机变量VIRE中的各种障碍物,MARC及其改进的算法,使读者阅读能力减少,影响最近标签的选择,然后使系统的定位精度降低。本文提出了一种新的改进计划。首先,通过高斯滤波器预处理RSSI,然后设置自适应阈值,并且通过牛顿插值方法获得虚拟参考标签的RSSI值。然后通过位置校正校正定位结果。同时,设置边界虚拟参考标签,通过这些方法改进了RSSI的准确性,并且参考标签的覆盖率增加。仿真结果表明,改进的算法具有较高的定位精度和比Landmarc和Vire算法更强的稳定性。

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