Receiver Strength Signal Indication based Wireless Sensor Networks offer a cheap solution for location-aware applications. For a final breakthrough these systems need fast deployment and easy auto-configuration. In this study, we use the real-life iMinds test bed to expand a two-dimensional localization algorithm to the pseudo third dimension with very low additional computational time. Our experiments show that this fast three-dimensional algorithm has no outliers and avoids manual calibration. Our algorithm has lower position errors than a maximum likelihood algorithm with a mean square error cost function. Furthermore, with non-parametric statistical tests, we show that our previously designed two-dimensional preprocessing performs equally well in pseudo-three dimensions: the preprocessing reduces the position error in a statistically significant way. Copyright (c) 2013 John Wiley & Sons, Ltd.