基于双线性插值与K-means聚类算法结合的位置指纹定位改进算法Improved location fingerprint position algorithm based on the combination of bilinear interpolation and K-means clustering algorithm
张蕊;张业荣;
摘要(Abstract)：
为了提升可见光通信(VLC)室内环境下的定位精度,提出一种基于双线性插值与K-means聚类算法结合的位置指纹定位改进算法。该算法首先建立初始指纹,然后对待定位点所在聚类域中的指纹进行插值计算,最后将插值后的部分区域指纹作为参考指纹库存,选择一种匹配算法实现最终定位。在5 m×5 m×3 m的室内房间建立VLC系统模型,仿真分析了指纹密集度对定位精度的影响以及改进算法的定位精度对比情况。仿真结果表明:随着指纹库密集度的降低,定位精度随之提高;改进算法使用插值指纹库与比使用初始指纹库的定位精度提高了21.5%,同时大大降低了计算复杂度。
关键词(KeyWords)： 室内可见光定位;发光二极管;位置指纹法;指纹库密集度;K-means聚类算法;双线性插值法
基金项目(Foundation):
作者(Authors): 张蕊;张业荣;
DOI: 10.13921/j.cnki.issn1002-5561.2022.05.008
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