基于无迹卡尔曼滤波的室内超宽带跟踪算法

郑州轻工业学院电气信息工程学院, 河南郑州 450002
基金项目:国家自然科学基金地区联合基金项目（U1504604）；国家自然科学基金青年科学基金项目（61501252）；河南省省院科技合作项目（122106000049）；郑州市UWB实时定位系统院士工作站项目（131PYSGZ211）；郑州轻工业学院2014年度研究生科技创新基金资助项目
中图分类号:TP92

UWB indoor tracking algorithm based on UKF

College of Electric and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Received Date:2016-01-12
Available Online:2017-01-15
CLC number:TP92

摘要:为解决移动目标在室内跟踪定位误差较大的问题，提出了一种基于无迹卡尔曼滤波（UKF）的超宽带（UWB）跟踪定位算法.该算法在定位阶段联合到达时间（TOA）与接收信号强度（RSS）两种定位算法的优势以获得较高的定位精度；在跟踪阶段，将TOA-RSS联合定位算法获得的量测值进行UKF估计，以得到移动目标的跟踪轨迹.仿真结果表明，该算法室内滤波误差与均方根误差均比同样使用TOA-RSS定位方法而采用扩展卡尔曼滤波（EKF）估计算法有一定程度的降低，跟踪定位精度有较大提高.
- 超宽带/
- 目标跟踪/
- 无迹卡尔曼滤波/
- 扩展卡尔曼滤波/
- TOA-RSS
Abstract:In order to solve the problem of the errors of moving target tracking in indoor positioning, the ultra wide band tracking localization algorithm was proposed based on unscented Kalman filter (UKF). In indoor positioning, a combination of TOA and RSS path loss model was used to estimate a targets position to get a higher positioning accuracy; In the tracking phase, the measured values obtained by the TOA-RSS joint localization algorithm were estimated by UKF to obtain the tracking trajectory of the moving target. The simulation results showed that the filtering error and root mean square error had a certain degree of reduction and the tracking and positioning accuracy was greatly improved when TOA-RSS joint localization algorithm was estimated by EKF.
- ultra wide band (UWB)/
- target tracking/
- unscented Kalman filter (UKF)/
- extended Kalman filter (EKF)/
- time of arrival-received signal strength (TOA-RSS)
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沈阳化工大学材料科学与工程学院沈阳 110142

基于无迹卡尔曼滤波的室内超宽带跟踪算法

UWB indoor tracking algorithm based on UKF

计量

通讯作者:陈斌, bchen63@163.com

基于无迹卡尔曼滤波的室内超宽带跟踪算法

English Abstract

UWB indoor tracking algorithm based on UKF

目录

基于无迹卡尔曼滤波的室内超宽带跟踪算法

UWB indoor tracking algorithm based on UKF

计量

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通讯作者:陈斌, bchen63@163.com

基于无迹卡尔曼滤波的室内超宽带跟踪算法

English Abstract

UWB indoor tracking algorithm based on UKF

目录