摘要
在无线传感器网络节点定位算法中,近似三角形内点测试(APIT)算法具有较好的定位性能,成本较低,实现容易,在节点密度比较密集的情况下能达到比较理想的定位精度。但是在节点相对稀疏的环境下该算法误判率高,误差较大。提出一种APIT改进算法,利用角度求和来判断未知节点位置,通过理论分析比较和仿真实验表明:该算法可以在节点相对稀疏的情况下减小定位误差,提高定位精度。
In the node localization algorithm for wireless sensor networks,APIT algorithm has good positioning performance,relative low cost,easy to realize and can achieve the ideal positioning precision in the intensive node density.However,in relative sparse node density environment,the algorithm is prone to errors.An improved APIT algorithm which can judge the localization of unknown node by summation of angle is presented.The simulation show that this algorithm can reduce errors and improve the positioning precision in relative sparse node density environment.
出处
《传感器与微系统》
CSCD
北大核心
2013年第1期73-75,共3页
Transducer and Microsystem Technologies
基金
江西省教育厅资助项目(GJJ10492)
