Adaptive range-based localization algorithm based on trilateration and reference node selection for outdoor wireless sensor networks

Abstract

Locating the nodes of outdoor wireless sensor networks (WSNs) using (tri)lateration with a low-cost ranging technique, such as the received signal strength indicator (RSSI), often results in inaccurate location estimates. This can mostly be explained by the combined effect of distance estimate errors and localization geometry, both of which are subject to the reference nodes used. To develop techniques for reducing localization error, the distance estimate errors and localization geometry must be analyzed and taken into account. To address these challenges, this paper aims to seek ways to improve the quality of range-based trilateration localization for WSN nodes in varying outdoor conditions. Based on simulations, we analyze the effects of ranging error and localization geometry on localization error. For that purpose, we introduce a simple measure to evaluate the geometry of reference triangle (GRT). To improve localization accuracy and precision, we propose an adaptive range-based localization (ARBL) algorithm that is based on trilateration and reference node selection. In ARBL, the GRT values are calculated for each 3-combination of a preselected reference node set, based on which the combinations are selected. The algorithm exploits these reference node 3-combinations aiming to find the best ones at a given time using a selection criteria that is based on ranging error and localization geometry. The simulation and experimental results indicate that the proposed algorithm reduces localization error considerably. This shows that it is possible to achieve sufficient localization accuracy using range-based trilateration localization, even based on the RSSI in challenging outdoor conditions, by employing applicable techniques and information.