Particle Filter Localization using a Hybrid Sub-6 GHz and mmWave System

Indoor localization has attracted considerable attention in recent years, driven by the growth of Internet of Things (IoT) applications. The transition of wireless communication systems toward higher frequency bands has further enabled higher accuracy user positioning. Various positioning methods have emerged over the years, supporting different levels of accuracy. In this work, we leverage measurements from multiple wireless communication technologies to address a dynamic positioning scenarios. We employ a Particle Filter (PF) to combine Time-of-Arrival (ToA) estimates from Sub-6 GHz and mmWave technology to enhance the localization accuracy in an indoor environment. Additionally, we evaluate the performance of the proposed algorithm by examining the positioning error statistics in different scenarios. Simulation results indicate that the proposed hybrid algorithm improves the mean localization and tracking error by approximately 42.8% and 17.8%, in comparison to the individual use of Sub-6 GHz and mmWave positioning technologies, respectively. The combination of these estimates results in a mean absolute positioning error better than 10 cm.

Particle Filter Localization using a Hybrid Sub-6 GHz and mmWave System

Ramya Vasist, IHP - Leibniz-Institut für innovative Mikroelektronik; Vladica Sark, Leibniz-Institut für innovative Mikroelektronik; Jesus Gutiérrez, IHP; Eckhard Grass, IHP, Germany and HU, Berlin