Indoor wireless ranging localization is a promising approach for low-power and high-accuracy localization of wearable devices. A primary challenge in this domain stems from non-line of sight propagation of radio waves. This study tackles a fundamental issue in wireless ranging: the unpredictability of real-time multipath determination, especially in challenging conditions such as when there is no direct line of sight. We achieve this by fusing range measurements with inertial measurements obtained from a low cost Inertial Measurement Unit (IMU). For this purpose, we introduce a novel asymmetric noise model crafted specifically for non-Gaussian multipath disturbances. Additionally, we present a novel Levenberg-Marquardt (LM)-family trust-region adaptation of the iSAM2 fusion algorithm, which is optimized for robust performance for our ranging-IMU fusion problem. We evaluate our solution in a densely occupied real office environment. Our proposed solution can achieve temporally consistent localization with an average absolute accuracy of ∼0.3m in real-world settings. Furthermore, our results indicate that we can achieve comparable accuracy even with infrequent (1Hz) range measurements.
@article{arxiv.2309.08803,
title = {Robust Indoor Localization with Ranging-IMU Fusion},
author = {Fan Jiang and David Caruso and Ashutosh Dhekne and Qi Qu and Jakob Julian Engel and Jing Dong},
journal= {arXiv preprint arXiv:2309.08803},
year = {2023}
}