计算机应用研究2017，Vol.34Issue(7)：2016-2018,3.DOI:10.3969/j.issn.1001-3695.2017.07.021
一种改进的基于KNN的动态预测指纹定位算法
Improved dynamic prediction fingerprint localization algorithm based on KNN
卢选民 1院文乐 1邱杨 1杨帆1
作者信息
- 1. 西北工业大学 电子信息学院, 西安 710072
- 折叠
摘要
Abstract
Because there are some problems in Wi-Fi indoor positioning system such as the low positioning accuracy and the instability positioning results,in order to improve these unstable factors,the paper deeply studied KNN fingerprint localization algorithm and improved the algorithm according to the characteristics of signal propagation volatile in the indoor environment.The algorithm found the nearest neighbor through dynamically predicting node position and filtering out the RP without similarity RSS vector at labels from wireless map in order to reduce time and computational complexity of the algorithm KNN.The experimental results show that the improved algorithm has been greatly improved in terms of location accuracy.Therefore,it is concluded that the improved KNN algorithm can improve the accuracy of positioning,which can reduce the mean error of position drift and positioning.关键词
室内定位/K最近邻/Wi-Fi定位/指纹定位/安卓/RSS向量Key words
indoor positioning/KNN/Wi-Fi positioning/fingerprint positioning/Android/RSS vector分类
信息技术与安全科学引用本文复制引用
卢选民,院文乐,邱杨,杨帆..一种改进的基于KNN的动态预测指纹定位算法[J].计算机应用研究,2017,34(7):2016-2018,3.
