Research on Indoor UWB Positioning Based on Expectation Maximization in NLOS Environment

被引：6

作者：

Zhou, Taoyun ^{[1
,2
]}

Xiao, Minlei ^{[1
]}

Liu, Yangyang ^{[2
]}

Cheng, Yun ^{[1
]}

Liu, Yi ^{[1
]}

机构：

[1] Hunan Univ Humanities Sci & Technol, Sch Informat, Loudi, Peoples R China

[2] Northwestern Polytech Univ, Sch Elect & Informat, Xian, Peoples R China

来源：

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE | 2021年 / 33卷 / 17期

基金：

中国国家自然科学基金;

关键词：

expectation maximization (EM); indoor positioning; time difference of arrival (TDOA); ultra-wide band (UWB); TARGET LOCALIZATION; COOPERATIVE LOCALIZATION; IDENTIFICATION; MITIGATION; ESTIMATOR;

D O I：

10.1002/cpe.6278

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Ultra-wide band (UWB) technology is especially suitable for indoor positioning because of its strong anti-interference ability, it can achieve centimeter-level positioning accuracy in the line of sight (LOS) environment, but it is challenging to construct a robust and high-precision algorithm in indoor complex and changeable environments. Therefore, it establishes an improved standard Kalman filter (SKF) based on expectation maximization (SKF-EM), which models the prediction error covariance and measurement noise using the maximum likelihood criterion, estimates the filter parameters online through the expectation maximum theory, and updates the Kalman filter gain according to the Kalman filter based on dropped measurements method (SKF-DMM). Experimental results show that: in case of serious occlusion, the maximum positioning error of SKF-EM algorithm is 1.03 m, 39% lower than that of SKF and 60.2% lower than that of UWB.

引用

页数：12

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