Demonstration Abstract: Collaborative Localization Using Inter-device Particle Filter Data Fusion

A lot of recent researches have addressed indoor localization by integrating portable/wearable communication and sensing technologies. While GPS dominates outdoor localization, indoor localization schemes have to consider different types of observations [1] and even use hybrid techniques [4] to fuse various sensor inputs. In this work, we observe that via M2M communications, when two devices meet up, which we call ”M2M encountering”, they can collaboratively calibrate each other’s location instantly. For instance, when applying Particle Filter (PF), a widely used fusing technique, on inertial sensing data, the localization result may diverge over time. We propose a concept called inter-PF, which takes M2M encountering opportunity to conduct a ranging action between two PFs, and show that it can converge the positioning results more rapidly, hence providing higher accuracy.