Indoor Location Estimation Based on Toa Data and Bias Estimation Using Gamma Regression

Abstract

We aim at improving the accuracy of indoor position estimation through a statistical approach. In this study, we propose a position estimation method based on Time-of-Arrival (ToA). ToA data are often useful. However, ToA data include a positive bias due to the reflection of radio waves. Therefore, it is difficult to estimate the TAG position from ToA data directly without an accurate bias correction. In this paper, we propose a maximum likelihood estimation method for the TAG position using gamma regression and a rotated distribution, and we show that the estimation with bias correction is more accurate than the estimation without bias correction. In addition, we show that our method also provides a confidence region for the TAG position.