WLS Localization Using Skipped Filter, Hampel Filter, Bootstrapping and Gaussian Mixture EM in LOS/NLOS Conditions

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초록

We present robust range-based localization algorithms for which range measurements are used to estimate the location parameter. Non-line-of-sight (NLOS) propagation of signal can deteriorate the estimation performance severely in the indoor and crowded urban areas. A study for localization has been intensively performed in the line-of-sight (LOS) conditions, but the work for the positioning in the mixed LOS/NLOS environments is comparatively rare. Thus, we aim at the robust localization in the LOS/NLOS mixture environments. The Hampel and skipped filters-based weighted least squares (WLS) methods are proposed for situations where the variance for inliers is unknown in LOS/NLOS mixture environments. For the unsupervised clustering algorithm, Gaussian mixture expectation maximization-based WLS algorithm is utilized. It is demonstrated that the positioning accuracy of the proposed methods is higher than that of conventional methods through extensive simulation.

키워드

LocalizationrobustHampel filterskipped filterclusteringweighted least squaresTOA-BASED LOCALIZATIONNLOS ERROR MITIGATIONGEOLOCATIONESTIMATOR
제목
WLS Localization Using Skipped Filter, Hampel Filter, Bootstrapping and Gaussian Mixture EM in LOS/NLOS Conditions
저자
Park, Chee-HyunChang, Joon-Hyuk
DOI
10.1109/ACCESS.2019.2905367
발행일
2019-03
유형
Article
저널명
IEEE Access
7
페이지
35919 ~ 35928

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