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作 者:陈德全 CHEN Dequan(College of Computer,Chongqing University,Chongqing 400044,China;General Education Department,Chongqing Preschool Education college,Chongqing 404047,China)
机构地区:[1]重庆大学计算机学院 [2]重庆幼儿师范高等专科学校通识教育部
出 处:《传感技术学报》2019年第12期1870-1874,共5页Chinese Journal of Sensors and Actuators
基 金:重庆市科研课题项目(193395)
摘 要:近期,基于移动单元的无线定位方案受到广泛关注。然而,现存的定位方案假定移动单元位置已知、无线传播模型的参数已知,这与事实并不相符。为此,提出基于半定规划的移动辅助定位(Semi-Definite Programming based Mobility-Assisted Localization,SMAL)算法。移动单元沿着任意轨迹移动,并周期向传感节点传输beacon包。锚节点从移动单元接收信号,并依据接收beacon的信号强度的相似性估计节点间距离。最后,依据距离值,并结合半定规划算法估计节点位置。仿真结果表明,相比于静态定位算法,SMAL算法能够获取高的定位精度。In recent years,much attention has been paid to wireless localization schemes that exploit receptions of messages sent by a mobile unit.However,existing methods assume an accurate knowledge of the location of the mobile unit and a precise propagation model of the actual radio environment.This does not tally with the facts.Therefore,Semi-Definite Programming based mobility-assisted localization(SMAL)is proposed in this paper.In SMAL,a mobile unit moving along an arbitrary trajectory broadcasts beacons periodically to all sensor nodes.Receiving messages sent from a mobile unit,anchor nodes estimate an inter-node distance using a similarity between received signal strength indicators of beacons received from the mobile unit.Finally,according to the distance value and the semi-definite programming algorithm,the node location is estimated.Simulation results show that the proposed SMAL algorithm achieve a very high localization accuracy while static localization techniques fail.
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