摘要
针对室内定位中接收信号强度指示(RSSI)受到环境干扰波动大,使得定位精度低且不稳定,但是单一滤波算法较难实现有效滤波的问题,本文提出基于中值和滑动窗口融合滤波的加权K最近邻(WKNN)定位算法,该算法分别用中值和滑动窗口对RSSI值进行滤波,再用卡尔曼算法对两种滤波结果进行融合,实现融合滤波,最后用基于动态权重的WKNN算法实现定位。实验结果表明,经过融合滤波处理RSSI后,定位的平均误差为0.946 m,定位精度优于单一滤波且更稳定。
Aiming at the problem that the received signal strength indication(RSSI)fluctuates greatly due to environmental interference in indoor positioning,which makes the positioning precision low and unstable,but it is difficult to achieve effective filtering by a single filtering algorithm,a weighted K-nearest neighbor(WKNN)localization algorithm based on median and sliding window fusion filtering is proposed.The algorithm filters the RSSI values with median and sliding window,respectively,then fuses the two filtering results with Kalman algorithm to achieve fusion filtering,and finally uses the WKNN algorithm based on dynamic weight to achieve localization.The experimental results show that after fusion filtering processing on RSSI,the average positioning error is 0.946 m.The positioning precision is better than that of single filtering and more stable.
作者
李小年
谭方
齐斐
杨永锋
姜汗涛
李芳芳
LI Xiaonian;TAN Fang;QI Fei;YANG Yongfeng;JIANG Hantao;LI Fangfang(School of Mathematics and Information Engineering,Longdong University,Qingyang 745000,China)
出处
《传感器与微系统》
北大核心
2025年第5期142-145,共4页
Transducer and Microsystem Technologies
基金
甘肃省科技计划项目(23JRZA494)
甘肃省庆阳市科技计划项目(QY-STK-2022A-020,QY2021A-G001,QY2021A-S073,QY-STK-2022A-086)
甘肃省高校教师创新基金项目(2023A-148)
陇东学院青年科技创新项目(XYZK2201,XYZK2204,XYBYZK2307,XYZK2305,XYZK2405)。
关键词
室内定位
融合滤波
接收信号强度指示
加权K最近邻
indoor positioning
fusion filtering
received signal strength indication
weighted K-nearest neighbor
