摘要
针对基于接收信号强度(received signal strength,RSS)测距定位框架,提出基于贝叶斯测距和迭代最小二乘定位的RSS的定位算法.在测距阶段,先利用贝叶斯概率模型处理测距过程,并采用最小均方误差(minimum mean square error,MMSE)估计距离;在定位阶段,利用迭代最小二乘(iterative least square,ILS)估计节点的位置,最后重点对其定位性能做了理论分析和对比实验.仿真结果表明,提出的MMSE+ILS定位的方案极大地提高了定位精度,并降低了计算复杂度,但运行时间略有提高.
In the framework of range-based localization from RSS（received signal strength）measurements,the Bayesian Ranging and Iterative Least Squares（ILS）positioning is proposed in this paper.In ranging phase,ranging is considered as a Bayesian estimation problem,and the distance is estimated by MMSE（minimum mean square error）.In positioning phase,,ILS is used to update the estimated of unknown position.Numerical results show that the proposed algorithm improves considerably the accuracy of localization,and reduces computational complexity,but increases computation time.
出处
《西南师范大学学报（自然科学版）》
CAS
北大核心
2015年第9期23-29,共7页
Journal of Southwest China Normal University(Natural Science Edition)
基金
2014年度河南省科技计划项目(142102210224)
关键词
无线传感网络
贝叶斯估计
最小二乘
最大似然估计
最小均方误差
迭代最小二乘
wireless sensor network
Bayesian estimation
least squares
maximum likelihood
minimum mean square error iterative least square
