Ranging Based Wireless Positioning with Accurate Estimation of Bias Errors

In this paper, the problem of positioning a tag/receiver using range measurements is addressed. The performance of two linear least-squares estimators in terms of positioning accuracy is considered. To further improve the accuracy, we propose two measures in order to remove measurement noise and outliers, and to reduce measurement bias errors. Noise and outliers are removed by applying a recursive average filter to the measurements. Thus, the remaining errors are mainly systematic, i.e. bias errors. A direct positioning method is then developed to enable estimating the average measurement bias. These two procedures have a positive impact on the positioning accuracy as is demonstrated by the experiment. Filtering has reduced maximum errors by at least 25%. Bias reduction further decreased the mean and maximum errors by at least 66% and 42% respectively.