摘要
无线传感网中的多类应用均需要准确的定位算法。为了降低定位成本,减少能量消耗,常采用基于接收信号强度RSS(Received Signal Strength)测距,再利用最大似然ML(Maximum likelihood)估计算法求解节点的位置。然而,ML估计为非线性、难以获取全局最优解。为此,提出二阶锥规划SOCP(Second-order Cone Programming)的RSS测距的定位方案。利用SOCP将ML估计转换成SOCP优化问题,再引用最小二乘法简化目标函数,最终建立SOCP表达式,最后利用CVX求解。仿真结果表明,提出的SOCP算法的定位精度比SD/SOCP-2、SDPRSS平均提高了近15%至20%。
In the wireless sensor networks,location based applications require an accurate localization algorithm. To locate sensors at a low cost,the received signal strength(RSS)based ML(Maximum likelihood)estimator is used to localization. However,the difficulties in the ML problem are overcome by transforming the original nonlinear problem into a convex one,which is difficult to solve the globally optimal solution. Therefore,the Second-order Cone Programming(SOCP)localization scheme is proposed in this paper. ML estimator is transformed into SOCP optimal problem by SOCP.It uses least squares(LS)to simplify the objective function,finally form the SOCP function,which can be readily solved by CVX. Simulation results show that the proposed SOCP algorithm outperform in term of the accuracy between 15-20%on average,compared with SD/SOCP-2 and SDPRSS.
作者
刘潇潇
LIU Xiaoxiao(Information Faculty,Business College of Shanxi University Taiyuan 030031)
出处
《办公自动化》
2018年第24期17-21,共5页
Office Informatization
基金
山西省自然科学基金(2012011013-2)(基于虚拟力算法的异构传感器网络节点分布技术的研究)
关键词
接收信号强度
二阶锥规划
最小二乘
定位
无线传感网
Received signal strength
Second-order cone programming
Least squares
Localization
Wireless sensor networks
