Node localization in wireless sensor network using dynamic distance prediction algorithm

Abstract

Wireless sensor network is characterized by low power, low cost and low complexity. With these features, wireless sensor network has great potential to develop indoor positioning system. At present, Circular line of position based on Received Signal Strength Indication (RSSI) has minimum additional cost and most simple algorithm among the existing location strategies. However, radio signal propagation is easily affected by diffraction, reflections, and also scattering of radio in the building. Consequently, the location strategies need good method to improve the accuracy of position estimation system. This paper uses dynamic distance prediction algorithm in Circular line of position, and then employs Zigbee as the wireless sensor network medium. After getting original RSSI value, location node selects the raw data with distance error function, and calculates the position by low error group of RSSI. Although the method increases the number of RSSI measuring, it can effectively eliminates RSSI value caused by signal fluctuation and improves the accuracy of traditional position estimation system by data selection. Simulation results show that the accuracy of distance estimates based on dynamic distance prediction has increased about 30%.