针对WLAN室内定位的移动AP筛选算法  

Mobile AP filtering algorithm based on WLAN Indoor Location

作　　者：苑豪 张现军[1] 李庆党 YUAN Hao;ZHANG Xianjun;LI Qingdang(College of Automation and Electronic Engineering,Qingdao University of Science and Technology,Qingdao 266042,China)

机构地区：[1]青岛科技大学自动化与电子工程学院,青岛266042

出　　处：《自动化与仪器仪表》2022年第4期21-24,共4页Automation & Instrumentation

摘　　要：由于现实定位场景内移动AP(access point)等因素的影响,基于位置指纹的WLAN室内定位精度难以保障。针对这一问题,本文提出一种在传统WLAN室内定位算法,不增添格外成本的移动AP筛选算法(RMAP),该算法通过在定位场景内划分区域,找到不同时间同一地点的信息,依靠AP的信号强度(RSS)与位置置信度之间的关系,实现数据增补从而筛选出场景内的移动AP,实验阶段通过实验场景测试了场景内移动AP的筛选结果,并用去除移动AP的指纹库测试了传统定位算法NN、KNN、WKNN,整体定位精度会显著提高。Due to the influence of mobile AP(access point) and other factors in the real positioning scene,the indoor positioning accuracy of WLAN based on location fingerprint is difficult to guarantee.To solve this problem,this removing a mobile AP screening algorithm(RMAP) without extra cost in the traditional WLAN Indoor Positioning Algorithm.The algorithm divides the area in the positioning scene,finds the information at the same place at different times,and realizes data supplement by relying on the relationship between the AP’s signal strength(RSS) and location confidence,so as to screen the mobile AP in the scene,In the experimental stage,the screening results of mobile AP in the scene are tested through the experimental scene,and the traditional positioning algorithms NN,KNN and WKNN are tested with the fingerprint database removing mobile AP.The overall positioning accuracy will be significantly improved.

关 键 词：WLAN室内定位 移动AP 区域坐标划分 RMAP KNN 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]