High-Precision RSSI-based Indoor Localization Using a Transmission Power Adjustment Strategy for Wireless Sensor Networks

Abstract

Indoor localization is an important issue in wireless sensor network (WSN) studies. Sensed data may become meaningless, if the locations of sensors are not known. Traditional localization techniques do not meet the requirements of low-cost and energy-conservation while performing localization tasks. Recently, the received signal strength indicator (RSSI)-based range measurement technology is widely used in sensor networks due to its easy implementation. In typical indoor environments, RSSI is affected by dense multipath fading effects because people are moving around, or because furniture and equipment block transmission signals. Therefore, the overall accuracy of RSSIbased localization schemes remains low. In this paper, a new localization scheme which is based on a transmission power adjustment strategy is proposed. Firstly, power decay curves are created in a real indoor environment to accurately estimate the distances between an unknown node and anchor nodes. Secondly, the unknown node selects three nearest anchor nodes by using the minimum transmission power to limit the estimated location to a triangle area. And then, the centroid of the triangle is calculated and serves as the initial estimated point. Finally, based on the estimated distances of corresponding power curves determined by RSSI scores using different transmission power levels, the final estimated location falls in one of the three equally divided areas of the triangle. The experimental results demonstrate that the proposed method can provide a low-cost solution for indoor localization with high precision.