基于聚类、空间分集和轨迹连续的实时定位算法  

Real-time Positioning Algorithm Based on Clustering,Spatial Diversity and Continuous Trajectory

作　　者：陈业纲[1] 徐则同[2] 

机构地区：[1]长江师范学院计算机工程学院,重庆408000 [2]中国科学院数学与系统科学研究院,北京100190

出　　处：《计算机科学》2015年第8期283-287,299,共6页Computer Science

基　　金：教育部春晖计划:基于Zigbee的乌江涪陵到武隆段排污口污水实时监测系统的研究资助

摘　　要：针对多样本消除接收信号强度其时域浮动易造成定位的更新率下降和实时性降低的问题,首先在定位阶段利用空间分集技术,建立相邻位置信号强度的矢量队列来计算当前位置的强度;然后利用轨迹的连续性质,消除时域浮动产生的定位误差,同时通过对指纹数据库进行聚类,在对目标定位时只需在较小的聚类集合中进行少量计算,无需遍历整个数据库,且计算量不随指纹数据库的增大而增加,极大地降低了计算量;最后进行了实验仿真,结果表明该算法能有效减小运算量和定位误差。As the elimination of received signal strength samples in time domain is easy to cause the location update rate floating reduction and real-time problem, we first used space diversity technology in positioning stage, and built vector queue of adjacent position signal strength to calculate the strength of current position. Then we used the continuous nature of track to eliminate the location error produced by time floating, at the same time by clustering the fingerprint database, the target localization was performed only a small amount of calculation in the smaller cluster set, without the need to traverse the entire database. And the calculation does not increasesas the fingerprint database increases, which greatly reduces the amount of calculation. Finally the simulation and experiments show that the algorithm can reduce the amount of calculation and positioning error effectively.

关 键 词：接入点 基于位置的服务 扫描点 接收信号强度 空间信号最近邻法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]