OWP-IMU: An RSS-Based Optical Wireless and IMU Indoor Positioning Dataset

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 letter, we collected RSS values at a sampling frequency of $27 \,\mathrm{Hz}$, inertial measurement unit (IMU) at a sampling frequency of $200 \,\mathrm{Hz}$ and the ground truth at a sampling frequency of $160 \,\mathrm{Hz}$ in three indoor environments. The first scenario is obstacle-free, the second contains a metal column obstacle, and the third contains a letter rectangular obstacle, with both obstacles representing different non-line-of-sight (NLOS) scenarios. We recorded data with a vehicle at three different speeds (low, medium and high). The dataset includes over $160 \,{\mathrm{k}}$ data points and covers more than $110 \,\min$. 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 or transformer. The dataset OWP-IMU and accompanying benchmark results are open source to support further research on indoor localization methods.