%0 Journal Article
%T Multi-classification Algorithm for Indoor Positioning Based on Support Vector Machine<br>基于支持向量机多分类的室内定位系统
%A ZHU Yu-jia
%A DENG Zhong-liang
%A LIU Wen-long
%A XU Lian-ming
%A FANG Ling
%A <br>朱宇佳
%A 邓中亮
%A 刘文龙
%A 徐连明
%A 方灵
%J 计算机科学
%D 2012
%I 
%X A multi-classification algorithm for indoor positioning based on SVM was proposed to tackle the problem of low precision and fluttering results faced in many real-time location systems. Traditional matching algorithms based on sampling points arc always deficient in dealing with nonlinear problem and jumping results in a short time. In handing this limitation,object location process was considered as a multi-classification problem by introducing grid concept K candidate grids were obtained using SVM first These candidates were then refined by previous location results, and ultimate accuracy result was achieved through a Kalman filter. Temporal information was utilized in the matching process to make the object movement more stable and smooth. Experiments show the superiority of our method over naive SVM method.
%K Support vector machine(SVM)
%K Grid
%K Real-time indoor location
%K Received signal strength indication(RSSI)
%K Kalman filter<br>支持向量机(SVM)
%K 网格
%K 室内实时定位
%K 接收信号强度(RSSI)
%K 卡尔曼滤波
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=5C6A9FB29B993220E6972A1F978B951C&yid=99E9153A83D4CB11&vid=7C3A4C1EE6A45749&iid=E158A972A605785F&sid=9971A5E270697F23&eid=6209D9E8050195F5&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0