RSSI-Based Indoor Localization Using Multi-Lateration With Zone Selection and Virtual Position-Based Compensation Methods

In the well-known and widely used multi-lateration method, an unknown target position is estimated using reference node positions and received signal strength indicator (RSSI) levels which indicate the distances between the target and the reference nodes. Since the RSSI signal in physical environments is time-varying and fluctuates overtime due to multi-path effects, RSSI signal variation can significantly cause localization errors. Inaccurate results can lead to poor decisions in the overall system. In this paper, an extended multi-lateration method is proposed to increase the localization accuracy. The novelty of the proposed method is that the boundary consideration, the zone selection, and the estimated position compensation method based on virtual positions are developed and integrated with the traditional multi-lateration method. To verify the proposed method, experiments using a ZigBee, 2.4 GHz, IEEE 802.15.4 wireless sensor network deployed in a laboratory room (the area size of 4 m x 4 m) and a corridor of the building (22 m x 9.3 m) have been tested. Experimental results demonstrate that all estimated positions of targets provided by the proposed method are within the test area (or zone), while the traditional multi-lateration method very often provides estimated positions outside the test area. The results also indicate that, by the proposed method, the estimation errors of most targets are lower than the case the multi-lateration method, and only a few targets, the errors by both methods are the same. Finally, in average, the proposed method significantly provides estimation errors lower than the traditional method: 0.682 m and 1.603 m, respectively (for the laboratory room), and 1.776 m and 4.353 m, respectively (for the corridor of the building). Here, the proposed method outperforms the traditional method by 57.430% and 59.194%, respectively.