无线传感器网络中APIT--VP三维定位算法
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摘要
在研究APIT—3D定位算法思想基础上,提出了一种改进的定位算法APIT—VP。新算法解决了APIT—3D算法在节点分布不均匀的情况下定位精度和定位覆盖率较低的问题;在一定程度上避免了PIT—3D测试中出现的OutToIn和InToOut误判错误;并且利用基于中垂面分割法代替原先的网格扫描算法,降低定位运算复杂度,减少能耗。仿真实验结果表明:在无线传感器网络环境理想、300个节点随机部署在100 m×100 m×100 m的三维区域情况下,APIT—VP算法定位覆盖率可达90%,定位误差控制在25%左右,并且与APIT—3D算法相比有效降低了计算复杂度。
On the basis of study of approximate point-in-tetrahedron 3D( APIT—3D) localization algorithm, present an improved localization algorithm,called APIT—VP. The new algorithm aims at solving the problem of low precision and low coverage rate of localization in APIT—3D algorithm when distribution of nodes is not uniform. To some extent,it also avoids misclassification errors including OutToIn as well as InToOut in PIT—3D test. At the same time,to reduce the computational complexity and to reduce energy consumption,the new algorithm uses space division and segmentation method based on the median plane instead of the original grid scanning algorithms. Simulation experimental results indicate that the positioning coverage rate is up to 90 % and positioning error is controlled about 25 % when 300 nodes are randomly deployed in 100 m × 100 m × 100 m 3D area scenarios,in addition, the computational complexity is effectively reduced compared with APIT—3D algorithm.
On the basis of study of approximate point-in-tetrahedron 3D( APIT—3D) localization algorithm, present an improved localization algorithm,called APIT—VP. The new algorithm aims at solving the problem of low precision and low coverage rate of localization in APIT—3D algorithm when distribution of nodes is not uniform. To some extent,it also avoids misclassification errors including OutToIn as well as InToOut in PIT—3D test. At the same time,to reduce the computational complexity and to reduce energy consumption,the new algorithm uses space division and segmentation method based on the median plane instead of the original grid scanning algorithms. Simulation experimental results indicate that the positioning coverage rate is up to 90 % and positioning error is controlled about 25 % when 300 nodes are randomly deployed in 100 m × 100 m × 100 m 3D area scenarios,in addition, the computational complexity is effectively reduced compared with APIT—3D algorithm.
引文
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[5]Zhou Yong,Xia Shixiong,Ding Shifei.An improved APIT node self-localization algorithm in WSNs based on triangle-center scan[J].Journal of Computer Research and Development,2009,16(4):566-574.
[6]刘玉恒,蒲菊华,赫阳,等.无线传感网络三维自身定位方法[J].北京航空航天大学学报,2008,34(6):647-651.
[7]刘志强,王行甫.基于中垂面分割的WSNs三维定位方法[J].计算机工程,2010,36(14):90-92.
[2]Zhang Jianping,Yu Min,Zhang Ke,et al.An improved weighted triangle centroid localization algorithm of APIT for wireless sensor networks[C]∥2012 International Conference on Computer and Information Science,Safety Engineering,Wuhan,China:IEEE,2012:18-21.
[3]Zeng Fanzhen,Yu Min,Zou Chengwu,et al.An improved pointin-triangulation localization algorithm based on cosine theorem[C]∥2012 8th International Conference on Wireless Communications,Networking and Mobile Computing,Shanghai,China:IEEE,2012:1652-1655.
[4]Rong P,Sichitiu M.Angle of arrival localization for wireless sensor networks[C]∥Proc of SECON'06,Reston,USA:IEEE,2006:374-382.
[5]Zhou Yong,Xia Shixiong,Ding Shifei.An improved APIT node self-localization algorithm in WSNs based on triangle-center scan[J].Journal of Computer Research and Development,2009,16(4):566-574.
[6]刘玉恒,蒲菊华,赫阳,等.无线传感网络三维自身定位方法[J].北京航空航天大学学报,2008,34(6):647-651.
[7]刘志强,王行甫.基于中垂面分割的WSNs三维定位方法[J].计算机工程,2010,36(14):90-92.