TOA Wireless Positioning with a Mobile Anchor in Wireless Sensor Networks

In this paper, we propose a novel hybrid RSS/TOA positioning algorithm with a mobile anchor, which follows a spiral trajectory to cover the whole region of the wireless sensor networks (WSN). The conventional time of arrival (TOA) positioning algorithms have two considerable accuracy problems. Firstly, as the distance between the reference node and the sensor increases, its accuracy is degraded gradually. Secondly, when an obstacle exists between the reference node and the sensor, its accuracy is degraded greatly. In our proposed algorithm, the mobile anchor, which plays the same role as the reference node, moves on a spiral trajectory and transmits its signal periodically. The received signal strength (RSS) is utilized by the sensor not only to compute whether it is closed enough to the mobile anchor but also to distinguish the obstacle. As a result, the measurement range of the TOA ranging process is restricted within the interval of two adjacent spiral curves. Under the circumstance that no obstacle exists between the mobile anchor and the sensor, the TOA ranging process and the proposed two-step positioning calculation are operated to estimate the position of the sensor accurately. Simulations are performed to compare the performance of the proposed hybrid RSS/TOA positioning algorithm with the performance of the conventional TOA least square estimating positioning algorithm (TOA_LSE). Simulation results show that the average positioning error is reduced by 48.2% and the standard deviation of the positioning errors is reduced by 71.3%.This work was supported by the Brain Korea 21 Project in 2011. This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2012-C1090-1200-0010). This work was supported by the IT R&D program of MKE/KEIT. [10035570, Development of selfpowered smart sensor node platform for smart&green building]