With the development of the wireless network technology and the increment of the wireless network coverage, people demand more and more location information when they access to network resources anywhere, this promotes the progress of wireless location technology. Analyzes the log-normal distribution model and proposes Gaussian filtering method which is used to select RSSI value of the preferred node. Also obtain the path loss index values in specific environment. This can reduce the error affected by the RSSI value. Use the distance based on the RSSI to locate the unknown node. The weighting factors is determined by the distance obtained from the RSSI. The weighted centroid algorithm has high accuracy and wide range of practicality, nodes do not demand additional communication spending.%无线网络技术的发展和覆盖率的增加,使得人们在随时随地使用无线网络资源时,对基于位置的信息需求越来越多,这推动了无线定位技术的研究进展.文中通过分析对数-常态分布模型,提出用高斯滤波法优选节点的RSSI值,并通过实地采集数据,得到了在特定环境下的路径损耗指数值,以减小由于RSSI值的影响产生的误差.结合加权质心法进行节点定位,加权因子由RSSI测距法得的距离决定.加权质心算法具有较高的精度,整个定位过程中节点间无需额外的通信开销,具有广泛的实用性.
展开▼
