# Robust Indoor Localization with Ranging-IMU Fusion

arXiv: https://arxiv.org/abs/2309.08803 · HTML: https://mlsanity.com/paper/2309.08803/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Sep 2023.

## Built on by (most cited first, 3 of 3)

- [Suite-IN: Aggregating Motion Features from Apple Suite for Robust Inertial Navigation](https://mlsanity.com/paper/2411.07828/) (2024)
- [GNSS Jammer Direction Finding in Dynamic Scenarios Using an Inertial-based Multi-Antenna System](https://mlsanity.com/paper/2512.05128/) (2025)
- [Suite-IN++: A FlexiWear BodyNet Integrating Global and Local Motion Features from Apple Suite for Robust Inertial Navigation](https://mlsanity.com/paper/2504.00438/) (2025)

## Abstract (arXiv)

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.