Localization techniques for traffic applications based on robust WECOLS positioning in wireless sensor networks

Abstract

We consider localization techniques based on wireless sensor networks (WSN), which are a promising technology to achieve highly accurate positioning solutions. Hence, this paper provides an overview of the concept of localization in modern railway applications, e.g. locating trains in storage sidings. Different geometrical scenarios are analyzed by using real measurement data. Generally, position estimation in WSNs is based on distance measuring by means of time-of-flight (TOF) ranging techniques. To employ radio frequency - (RF) based positioning here, we introduce weighting combinations least squares (WECOLS), an extended LS positioning approach, for computing positions by determining the space of possible estimations generated from the input data. Furthermore we investigate WECOLS according to accuracy compared with LS and least median squares (LMS).