改进的狭长空间中加权质心定位算法

针对目前狭长空间环境中信号多路径效应明显、传感器节点定位精度不足等情况,提出了一种基于信号接收强度(RSSI)的加权质心定位算法.该算法根据狭长带状区域环境特点部署信标节点,通过相邻信标节点的实际距离和信号接收强度,动态获取周围环境的路径衰落指数,提高RSSI测距算法的环境适应能力;根据当前环境改进加权质心算法的加权因子,引入修正因子,进一步提高算法的定位精度.理论分析和仿真结果表明,该算法设计优化,适应于狭长空间环境,宽度分别为3 m、5 m、8 m、10 m,信标节点的个数为10的巷道环境中,其定位计算精度比传统加权质心算法分别提高了22.1%、19.2%、16.1%、16.5%,稳定性分别提高了23.4%、21.5%、18.1%、15.4%.

Improved weighted centroid localization algorithm in narrow space

Concerning the problem that severe signal multipath effect, low accuracy of sensor node positioning, etc. in narrow space, a new method using Weighted Centroid Localization (WCL) algorithm based on Received Signal Strength Indicator (RSSI) was proposed. The algorithm was used in scenarios with characteristics of long and narrow strip space, and it could dynamically acquire the decline index of path by RSSI and distance of neighbor beacon node signal, improve the environmental adaptation of RSSI distance detection algorithm. In addition, the algorithm based on environment improved weight coefficient of weighted centroid algorithm by introducing correction factor, which improved the accuracy of localization. Theoretical analysis and simulation results show that the algorithm has been optimized to adapt to narrow space. As compared with the Weighted Centroid Localization (WCL) algorithm, in roadway environment with the width of 3 m, 5 m, 8 m, 10 m respectively and 10 beacon nodes, positioning precision increases 22.1%, 19.2%, 16.1% and 16.5% respectively, the stability increases 23.4%, 21.5%, 18.1% and 15.4% respectively.