摘要
针对无线传感网络(WSNs)在测距误差影响下存在的节点定位精度问题,提出一种基于改进型粒子群优化的自定位方法。该方法利用未知节点与邻近锚节点之间的距离信息,通过具有跳出局部最优能力的改进型粒子群优化算法取得未知节点的位置。仿真结果表明,该算法与最小二乘估计法相比,具有较高的定位精度和较快的定位速度,且性能稳定,是一种可行的WSNs节点定位解决方案。
Aiming at the problem of node localisation precision under the influence of ranging error in wireless sensor networks（ WSNs）, a new self-localisation method based on modified particle swarm optimisation is proposed. The new method uses range information between the unknown node and the nearby anchor node and gets the unknown node location through the modified particle swarm optimisation with local prematurity prevention ability. Simulation results show that,the modified particle swarm optimisation,compared with the least square estimation method,has higher accuracy and speed in localisation as well as stable performance. It is a feasible WSNs node positioning solution.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第4期69-72,共4页
Computer Applications and Software
基金
山西省自然科学基金项目(2011011011-1)
关键词
粒子群优化算法
无线传感器网络
节点定位
非一致性变异
Particle swarm optimisation Wireless sensor networks Node localisation Inconsistent mutation
