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Robust Indoor Localization with Ranging-IMU Fusion

Fan Jiang, David Caruso, Ashutosh Dhekne, Qi Qu, Jakob Engel, Jing Dong

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Abstract

Indoor wireless ranging localization is a promising approach for low-power and high-accuracy localization of wear- able 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. Fur- thermore, our results indicate that we can achieve comparable accuracy even with infrequent range measurements down to 1Hz.

Index terms

Localization Sensor Fusion SLAM