OWP-IMU: An RSS-based Optical Wireless and IMU Indoor Positioning Dataset
Abstract
Received signal strength (RSS)-based optical wireless positioning (OWP) systems are becoming popular for indoor localization because they are low-cost and accurate. However, few open-source datasets are available to test and analyze RSS-based OWP systems. In this paper, we collected RSS values at a sampling frequency of 27 Hz, inertial measurement unit (IMU) at a sampling frequency of 200 Hz and the ground truth at a sampling frequency of 160 Hz in two indoor environments. One environment has no obstacles, and the other has a metal column as an obstacle to represent a non-line-of-sight (NLOS) scenario. We recorded data with a vehicle at three different speeds (low, medium and high). The dataset includes over 110 k data points and covers more than 80 min. We also provide benchmark tests to show localization performance using only RSS-based OWP and improve accuracy by combining IMU data via extended kalman filter. The dataset OWP-IMU is open source1 to support further research on indoor localization methods.
Keywords
Cite
@article{arxiv.2505.16823,
title = {OWP-IMU: An RSS-based Optical Wireless and IMU Indoor Positioning Dataset},
author = {Fan Wu and Jorik De Bruycker and Daan Delabie and Nobby Stevens and Francois Rottenberg and Lieven De Strycker},
journal= {arXiv preprint arXiv:2505.16823},
year = {2025}
}