Reference Selection for Hybrid TOA/RSS Linear Least Squares Localization

Linear least squares (LLS) estimation is a suboptimum but low-complexity localization method based on measurements of location-related parameters. It has been proved that selection of the reference anchor influences the LLS localization accuracy. In addition, hybridization of different types of measurements can fix the deficiencies of one type of measurements. In this paper, we proposed a new reference selection criterion for the hybrid TOA/RSS LLS localization technique (called H-LLSRS), which considers both measured ranges and the information about their coarse variances. Moreover, we consider a general scenario that variances of range measurements are different, and derive a weighted LLS (WLLS) estimator for hybrid TOA/RSS localization according to the information about the accurate ranging variances and the correlations among the observations. Simulation results show that if the RSS-based ranging variances are considerably larger than the TOA-based ranging variances, the H-LLS-RS localization technique yields better accuracy than the conventional LLS localization techniques. Furthermore, reference selection has no effect on the accuracy of WLLS localization technique.