摘要： 针对基于TOF测距的节点定位算法在稀疏网络中定位覆盖率较低的问题，对初始估计位置进行迭代求精，达到精度门限的升级为锚节点。如果网络中存在不良节点，对节点进行估计分类，并实现对不良节点的定位。仿真结果表明，在适当增加节点计算量和通信开销的条件下，可提高改进算法的定位覆盖率。
关键词:
无线传感器网络,
TOF测距,
不良节点,
定位覆盖率,
迭代求精,
泰勒级数
Abstract: Two steps are put forward to improve the poor localization coverage of the Time of Flight(TOF) range-based algorithm in the sparse network. The initial values of estimated node locations which achieve the accuracy threshold with the iterative refinement method upgrade to anchor nodes. If there is adverse nodes in the network, estimate their classification and compute the position. Simulation results show that the improved algorithm has obviously better localization coverage at the cost of increasing appropriate communication and computation.
Key words:
Wireless Sensor Network(WSN),
Time of Flight(TOF) ranging,
adverse node,
localization coverage,
iterative refinement,
Taylor series
中图分类号:
鲁旭阳, 张效义, 刘广怡. 稀疏无线传感器网络的节点自定位算法[J]. 计算机工程, 2012, 38(18): 83-86.
LU Xu-Yang, ZHANG Xiao-Xi, LIU An-Yi. Node Self-localization Algorithm for Sparse Wireless Sensor Network[J]. Computer Engineering, 2012, 38(18): 83-86.