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

Abstract

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.