Time-of-arrival source localization based on weighted least squares estimator in line-of-sight/non-line-of-sight mixture environments

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초록

In this article, we propose a line-of-sight/non-line-of-sight time-of-arrival source localization algorithm that utilizes the weighted least squares. The proposed estimator combines multiple sorted measurements using the spatial sign concept, Mahalanobis distance, and Stahel-Donoho estimator, that is, assigning less weight to the samples as they are far from the center of inlier distribution. Also, the eigendecomposition Kendall's tau covariance matrix is utilized as the scatter measure instead of the conventional median absolute deviation. Thus, the adverse effects by outliers can be attenuated effectively. To validate the superiority of the proposed methods, the root mean square error performances are compared with that of the existing algorithms via extensive simulation.

키워드

Weighted least squaresspatial signMahalanobis distanceStahel-Donoho estimatorline-of-sightnon-line-of-sightSTAHEL-DONOHO ESTIMATORWIRELESS NETWORKSNLOS ENVIRONMENTSCOVARIANCECRITERIONLOCATIONSYSTEMS
제목
Time-of-arrival source localization based on weighted least squares estimator in line-of-sight/non-line-of-sight mixture environments
저자
Park, Chee-HyunChang, Joon-Hyuk
DOI
10.1177/1550147716683827
발행일
2016-12
유형
Article
저널명
International Journal of Distributed Sensor Networks
12
12