Robust Localization Employing Weighted Least Squares Method Based on MM Estimator and Kalman Filter With Maximum Versoria Criterion

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초록

This study presents a robust two-step weighted least squares (WLS) localization algorithm using the MM estimator and the Kalman filter with the maximum Versoria criterion (MVC). An outlier-resistant statistic for the actual transformed distance is determined and the covariance matrix of the outlier-resistant statistic is calculated. This covariance matrix is used in the two-step WLS method. The simulation results demonstrate that the localization performances of the proposed algorithms outperform that of the conventional methods.

키워드

Kalman filters; Location awareness; Signal processing algorithms; Sensors; Indexes; Prediction algorithms; Covariance matrices; Impulsive noise; kalman filter; localization; MM estimator; robust; versoria function; NETWORKS
제목
Robust Localization Employing Weighted Least Squares Method Based on MM Estimator and Kalman Filter With Maximum Versoria Criterion
저자
Park, Chee-Hyun; Chang, Joon-Hyuk
DOI
10.1109/LSP.2021.3082329
발행일
2021-00
유형
Article
저널명
IEEE Signal Processing Letters
권
28
페이지
1075 ~ 1079