OWP-IMU: An RSS-based Optical Wireless and IMU Indoor Positioning Dataset
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866915298726117376 |
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| author | Wu, Fan De Bruycker, Jorik Delabie, Daan Stevens, Nobby Rottenberg, Francois De Strycker, Lieven |
| author_facet | Wu, Fan De Bruycker, Jorik Delabie, Daan Stevens, Nobby Rottenberg, Francois De Strycker, Lieven |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_16823 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | OWP-IMU: An RSS-based Optical Wireless and IMU Indoor Positioning Dataset Wu, Fan De Bruycker, Jorik Delabie, Daan Stevens, Nobby Rottenberg, Francois De Strycker, Lieven Signal Processing 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. |
| title | OWP-IMU: An RSS-based Optical Wireless and IMU Indoor Positioning Dataset |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2505.16823 |