Constrained Least-Squares Trilateration for Indoor Positioning System Under High GDOP Condition
Sy-Hung Bach, Soo-Yeong Yi
Abstract
The indoor positioning system (IPS) plays a crucial role in many applications of the Internet of Things (IoT). The trilateration is the most common and widely used method for the IPS because of its computational efficiency and ease of implementation. However, the accuracy of trilateration is affected by the geometric dilution of precision (GDOP). In this article, we propose a constrained least-squares trilateration (CLST) for the IPS that achieves high positioning performance with efficient computations even under severe GDOP conditions. The ultrawideband sensors are used to test the proposed positioning algorithm in this study. The positioning performance of the proposed method is demonstrated by simulations and experiments.