[1]黄 威,张玲华.基于 RSSI 的无线传感器网络室内定位算法研究[J].计算机技术与发展,2020,30(10):64-68.[doi:10. 3969 / j. issn. 1673-629X. 2020. 10. 012]
　HUANG Wei,ZHANG Ling-hua.A RSSI-based Two Targets Wireless Sensor Network Indoor Localization Algorithm[J].,2020,30(10):64-68.[doi:10. 3969 / j. issn. 1673-629X. 2020. 10. 012]
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基于 RSSI 的无线传感器网络室内定位算法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年10期
页码:
64-68
栏目:
智能、算法、系统工程
出版日期:
2020-10-10

文章信息/Info

Title:
A RSSI-based Two Targets Wireless Sensor Network Indoor Localization Algorithm
文章编号:
1673-629X(2020)10-0064-05
作者:
黄 威; 张玲华
南京邮电大学 通信与信息工程学院 江苏省通信与网络技术工程研究中心,江苏 南京 210003
Author(s):
HUANG Wei; ZHANG Ling-hua
Jiangsu Engineering Research Center of Communication and Network Technology, School of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications,Nanjing 210003,China
关键词:
无线传感器网络室内定位; 双目标; RSSI 方差侦测; 最小误差定位; 权重链路
Keywords:
indoor WSN localization; two targets; RSSI variance detection; minimum error localization; weighted links
分类号:
TP393
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 10. 012
摘要:
针对传统的室内定位算法要求被测对象携带有源的设备或者电子标签的局限,以及现有的无源室内定位大部分都是考虑单目标定位,或者是多目标一起移动的情况,设计了一种利用无线传感器网络的接收信号强度(RSSI)来实现双目标无源室内定位的算法。 该算法利用移动的物体会改变无线链路接受信号强度这一基本原理, 根据时间窗内 RSSI 方差的改变来侦测目标是否出现。 对于被侦测到的目标,首先根据 RSSI 单位时间窗内方差挑选出高于阈值的异常链路并赋予权重,再通过挑选法对异常链路进行分组, 然后通过最小误差法得到初级定位点,最后计算初级定位点附近的所有点,选出权重与距离平方累积误差最小的点,这些就是通过算法定位出的目标点。 仿真结果表明,被定位点与定位点之间距离小于 0.5 m 的可能性占所有仿真结果的 90%。
Abstract:
Aiming at the limitation of traditional indoor location algorithm,which requires the tested person or object to carry an active device or electronic tag, and the fact that most of the existing indoor device free passive localization is based on single target location or multiple targets moving together, we design a device free passive (DFP) method based on the received signal strength of wireless sensor network (WSN). We use the basic principle that a moving object will change the signal strength of the wireless link to detect the presence of a target according to the change of RSSI variance in the time window. For the detected targets,the abnormal links above the threshold are first selected according to the RSSI unit time window variance and weighted,and they are grouped by the selection method.Then,the primary localization point is obtained by the minimum error method. Finally,all the points near the primary localization point are calculated,and the points with the minimum cumulative error of weight and distance square are selected. These are the target points located by the algorithm. The simulation shows that the distance between the located point and the predicted point is less than 0.5 m, which accounts for 90% of all simulation results.
更新日期/Last Update: 2020-10-10