COLA: Complexity-reduced trilateration approach for 3D localization in wireless sensor networks

Localization has been an important topic in datacentric wireless sensor networks (WSNs) due to the special association between location information and the relevance of sensory data. Although most proposed approaches have been modeled for 2D space, a gradual but marked shift in the focus of 3D localization has taken place. While the 3D technique brings WSNs closer to reality, its complexity in computation and accuracy can be relatively high. In this paper, we propose a COmplexity-reduced 3D trilateration Localization Approach (COLA) based on RSSI values. Our goal is to lower the complexity by reducing 3D trilateration to 2D trilateration through the use of super anchor nodes-ones with pairwise positions whose coordinates only differ in the z-axis. In this paper, we conduct several empirical experiments in an indoor office setting, and evaluate our approach by comparison with a typical 3D trilateration algorithm. The results show that our approach outperforms the typical algorithm and yields more accurate results with lower computational cost.