Anchor Deployment Optimization for Range-Based Indoor Positioning Systems in Non-Line-of-Sight Environment

Abstract

Optimizing anchor deployment is critical to ensure the performance and positioning stability of indoor positioning systems in real-world applications. In this article, a new anchor deployment optimization method is proposed to enhance the positioning performance of range-based positioning systems in the non-line-of-sight (NLOS) environment without increasing the application cost. First, a new fitness function is proposed by simultaneously considering the mean geometric dilution of precision (GDOP) and the coverage of available positioning area in the indoor NLOS environment. Then, a search architecture based on a particle swarm optimization (PSO) algorithm is proposed to optimize anchor deployment. The initialization method of swarm’s position and velocity is given, and the calculation process of the search architecture is introduced in detail. The results obtained from numerical simulations and experimental investigations verified that, for range-based positioning systems in NLOS environment, the accuracy and stability can be significantly improved by optimizing the anchor deployment through our proposed method.