摘要
针对无线传感器网络中基于RSS的定位算法存在的不足,提出一种协同定位算法。该算法包含2个方面:一是引入参考信标节点,以增加节点定位的容错性;二是采用狄克逊(Dixon)检验法剔除异常RSS值,同时引入RSS标准差阈值和学习模型,减小基于RSS的测距误差,有效提高定位精度。通过仿真实验对算法性能进行了评估,结果表明,该算法定位精度得到了有效提高,健壮性和稳定性较好。
Aiming at the shortcomings of the existing RSS（received signal strength） based localization algorithm for wireless sensor networks（WSN）,a cooperative localization algorithm（CLA） is proposed.A reference anchor node is introduced to tolerant some minor error including the node position error.Dixon detection method is applied to remove abnormal RSS values,while the standard deviation threshold of RSS and learning model are introduced to reduce the RSS ranging error and effectively improve the precision.Simulation experiments are performed to evaluate the performance of the proposed algorithm.The results demonstrate that the localization accuracy is improved effectively,while the stability and robustness are better.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2012年第12期139-143,共5页
Journal of Chongqing University
基金
国家自然科学基金资助项目(60872038)
重庆市自然科学基金重点资助项目(CSTC2009BA2064)
关键词
无线传感器网络
协同定位
接收信号强度
wireless sensor networks
cooperative localization
received signal strength（RSS）
