摘要
针对蚁群定位算法可能出现局部最优解而导致定位不准确的问题,提出了无线传感器网络自适应蚁群定位算法。通过将节点估计坐标移动方向离散化,将传感器定位问题转换成离散组合最优问题。定位过程中通过聚度和信息权重对传感器节点估计坐标向各个方向移动的概率进行修正,解决了定位结果收敛于局部最优解的问题。仿真结果表明,自适应蚁群定位算法比传统蚁群定位算法具有更低的定位误差。
Focusing on the problem of local optimal result of ant colony localization algorithm,a localization algorithm based on adaptive ant colony optimization for wireless sensor networks is proposed.By discretization of node＇s estimated coordinate moving direction,the sensor localization problem is transformed to a discrete combinatorial optimization problem.The updating probability of sensor＇s estimated coordinate moving direction is modified by polymerization degree and information weight in localization process,the problem of localization result converging to local optimal result is solved.The simulation results show that the localization error of localization algorithm based on adaptive ant colony algorithm is lower than that of localization algorithm based on ant colony algorithm.
出处
《压电与声光》
CAS
CSCD
北大核心
2016年第1期178-182,共5页
Piezoelectrics & Acoustooptics
基金
河南省重大科技专项基金资助项目(121100111000)
河南省高等学校重点科研基金资助项目(15A520002)
关键词
无线传感器网络
自适应蚁群算法
组合优化
定位算法
定位误差
估计坐标
wireless sensor networks
adaptive ant colony algorithm
combinatorial optimization
localization algorithm
localization error
estimated coordinate
