摘要
针对移动无线传感网络,并基于到达时间TOA(Time-of-Arrival)的测距模型,分析利用传感节点的移动信息进行定位问题,提出基于二阶锥规划的分布式定位算法。推导最大似然ML(Maximum Likelihood)定位估计表达式;考虑到基于ML的协作定位的非凸性,选用二阶锥规划SOCP(Second-order Cone Programming)松驰技术求解。为了降低计算成本,采用分布式策略实施SOCP算法。实验数据表明,该算法减少了均方根误差,提高了定位精度。
For mobile wireless sensor network, we studied the problem of localization using mobile information of sensor nodes based on the time-of-Arrival(TOA) model. Then we proposed distributed localization algorithm based on second-order cone programming. The expression of maximum likelihood(ML) location estimation was derived. Considering the non-convexity of ML-based cooperative localization, we used the second-order cone programming(SOCP) relaxation technique to solve the problem. In order to reduce the computing cost, a distributed strategy was adopted to implement the SOCP algorithm. The experimental data show that the algorithm reduces the root mean square error and improves the localization accuracy.
作者
贺伟
梁潘
He Wei;Liang Pan(College of Electric Information and Automation , Aba Teachers University, Wenchuan 623002, Sichuan, China;Department of Aviation Manufacturing Engineering, Chengdu Aeronautic Polytechnic, Chengdu 610100, Sichuan , China)
出处
《计算机应用与软件》
北大核心
2019年第4期161-165,共5页
Computer Applications and Software
关键词
移动无线传感网络
定位
到达时间
最大似然估计
二阶锥规划
Mobile wireless sensor network
Localization
Time of arrival
Maximum likelihood estimation
Second-order cone programming
