摘要
传感器节点的自定位问题是无线传感器网络的重要研究内容之一.APIT是一种主要的非基于测距的定位算法.相对于其他非基于测距定位算法,APIT具有定位精度高、通信开销小等优点.但是,APIT要求有较高的锚节点密度,而且在APIT测试过程中,边界效应以及低邻居节点密度容易增加InToOut和OutToIn测试错误的发生次数.另外,APIT算法中的网格扫描算法对于OutToIn错误的容错性较差且其执行效率低.针对以上问题,提出了一种基于三角形重心扫描的改进APIT算法.首先,分析了APIT测试中的两种典型错误InToOut和OutToIn错误产生的原因,引入了对APIT测试方法的两处改进;然后,分析了网格扫描算法对节点定位精度和算法执行效率的影响,提出了一种三角形重心扫描法,有效改进了算法的定位精度和执行效率;最后,通过仿真实验验证了改进后的算法不但可以有效地减少InToOut和OutToIn两类错误发生的次数,提高平均定位精度,改善算法的性能,而且对OutToIn错误的容错性更强,执行效率更高,能够显著地提高节点的平均精度.
Node self-localization is one of the important research topics in WSN. APII is a major range-free localization algorithm. Compared with other range-free algorithms, APIT can achieve higher precision position estimation with small communication cost. However, APIT requires high anchor node density. Besides, in the process of APIT test, boundary effect and low neighbor node density can easily increase InToOut error and OutToIn error. Otherwise, the grid scan algorithm is inefficient and has a lower fault-tolerance to OutToIn error. In allusion to the problems mentioned above, an improved APIT algorithm based on triangle-center scan is proposed. Firstly, the reason for InToOut error and OutToIn error is analyzed and two improvements of APIT are introduced. Then, the effect of grid scan algorithm on the precision of position estimation and the algorithm＇s efficiency are analyzed, and a triangle-center scan algorithm is presented. Finally, simulation results show that the improved algorithm not only can reduce the IntoOut error and OutToln error effectively and improve the precision of position estimation, but also has a higher fault-tolerance to OutToIn error and can enhance the algorithm＇s efficiency.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2009年第4期566-574,共9页
Journal of Computer Research and Development
基金
国家自然科学基金项目(50674086)
国家教育部博士点基金项目(20060290508)
江苏省博士后科学基金项目(0701045B)
中国矿业大学科技基金项目(2007B017)~~
