摘要
针对移动无线传感网络(Wireless Sensor Networks,WSNs)的节点定位问题,提出基于半定规划的节点定位(Semi-Definite Programming Localization,SDPL)算法。SDPL算法考虑测移动节点与锚节点间的测距和测速这两项信息。先推导了在准确测距环境下的最大似然(Maximum Likelihood,ML)的位置估计,再利用SDP技术求解非凸优化的定位问题的近似解。同时,将SDPL算法扩展到噪声测速环境。仿真结果表明,移动信息对定位性能有重要的影响。
For node Localization in Mobile Wireless Sensor Networks(WSNs),Semi-definite Programming Localization(SDPL)algorithm proposed in this paper.SDPL algorithm takes into account the distance measurement and velocity measurement between mobile node and anchor node.We first derive the maximum likelihood(ML)location estimator for the case of error-free velocity measurements.As the corresponding optimization problems are non-convex,we resort to semi-definite relaxation(SDR)techniques to find approximate solutions to each problem using semi-definite programming(SDP).We then extend our results to the cases where the velocity measurements are subject to measurement errors.Our simulation results show that exploiting the mobility information in the localization process can significantly improve the performance of the sensor localization.
作者
马佩勋
洪贵华
MA Peixun;HONG Guihua(Changsha Social Work College,Software Institute,Changsha 410004,China;West Yunnan University,School of Information Science&Engineering,Lincang Yunnan 677000,China)
出处
《传感技术学报》
CAS
CSCD
北大核心
2019年第11期1725-1729,共5页
Chinese Journal of Sensors and Actuators
基金
2019年度中国残联研究课题项目(CJFJRRB04-2019)
关键词
移动无线传感网络
定位
最大似然估计
半定规划
测速
mobile wireless sensor network
localization
maximum likelihood
semi-definite programming
velocity measurements
