An experimental dataset for indoor localization using angle of arrival and RSS measurements

Indoor positioning systems based on Bluetooth 5.1 Direction Finding technology have recently attracted significant attention due to their capability to estimate the Angle of Arrival (AoA) of radio signals using commercial off-the-shelf devices. Despite this progress, the availability of large-scale, well-annotated experimental datasets collected under realistic conditions remains limited. This paper presents a comprehensive experimental dataset for indoor localization based on BLE 5.1 devices, providing synchronized azimuth and elevation AoA measurements together with Received Signal Strength (RSS) values and precise ground-truth annotations. Data were acquired in a 110 indoor environment with an adjacent corridor, deploying nine anchors in two configurations (wall-mounted and ceiling-mounted) and two wearable BLE tags. The campaign covers three scenarios: calibration (187 static reference points), static measurements with body orientation variations, and multiple mobility use-cases reproducing realistic walking patterns and posture changes. Overall, more than 4.5 million samples were collected. A preliminary analysis highlights the impact of anchor geometry, field of view, and body shadowing on angular accuracy. The dataset is publicly available and provides a comprehensive benchmark for evaluating angle-based localization, fingerprinting, filtering, and machine-learning approaches in realistic indoor environments.