摘要
传统的无线传感器网络节点定位算法假设节点间的最短路径长度与实际几何距离之间存在函数映射关系.然而对于布设在复杂区域的无线传感器网络而言,这种函数映射关系不再成立,直接应用传统定位算法将会带来较大的定位误差.针对复杂区域中各向异性的无线传感器网络节点定位问题,提出了一种基于参考节点凸包划分的测距无关定位算法CHP.首先,对参考节点进行凸包划分;然后,按照路径最短优先原则为待定位节点选择所属凸包;最后,依据待定位节点所属凸包内的参考节点对其进行定位,有效避免了复杂区域边界和障碍物对定位精度的影响.仿真实验结果表明:CHP算法与传统算法相比在定位精度以及误差抖动方面有了大幅改进;同时,CHP定位算法在执行过程中最大限度地降低了复杂区域边界和障碍物对定位的不利影响.
Traditional wireless sensor network localization algorithms are generally based on the assumption that there is a mapping function between measured distance and Euclidean distance for pair of wireless sensor nodes.This assumption however would not hold when wireless sensor networks are deployed into complex areas.Thus,directly applying traditional algorithms to these networks would result in a large localization error.To solve the localization problem in the anisotropic wireless sensor networks deployed in complex areas,a range-free localization algorithm based on convex-hull partitioning（CHP）is proposed.At first,all the reference nodes are divided to form different convex-hulls in the CHP.And then,each unknown node determines which convex-hull it belongs to.Finally,each unknown node computes its own location based on reference nodes in the convex-hull it belongs to.The CHP algorithm can effectively reduce the localization errors incurred by the boundary or barrier factors of complex area through theoretical analysis.The results from extensive simulations show that compared with traditional algorithms,the CHP algorithm significantly reduces the localization errors and error jitters.At the same time,the proposed CHP localization scheme minimizes the unfavorable effects brought by the boundaries or barriers of the complex area in the executing process.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2011年第3期364-373,共10页
Journal of Computer Research and Development
基金
国家"九七三"重点基础研究发展计划基金项目(2006CB303006
2011CB302905)
国家自然科学基金项目(60803009
60803116)
关键词
传感器网络
复杂区域
各向异性网络
凸包划分
定位算法
sensor networks
complex area
anisotropic networks
convex-hull partitioning
localization algorithm
