UaVirBASE: A Public-Access Unmanned Aerial Vehicle Sound Source Localization Dataset

UaVirBASE is a publicly available dataset designed for the sound source localization (SSL) of unmanned aerial vehicles (UAVs) using acoustic signals. It contains synchronized multi-microphone audio recordings collected under controlled experimental conditions, featuring a wide range of UAV positions and orientations with respect to a fixed microphone array. The dataset includes variations in: Distance and altitude from the array Azimuth angles UAV orientations (front, back, left, right) These variations are critical for training robust machine learning and deep learning models for SSL in real-world UAV scenarios. Additionally, this dataset is accompanied by detailed metadata and annotation files, as well as documentation outlining the recording setup, hardware specifications, and data acquisition pipeline. We provide a baseline deep neural network (DNN) model trained on UaVirBASE with performance metrics including: Mean Absolute Error (MAE) of 0.5 meters for distance/height ~1 degree azimuth error <10 degrees for side (orientation) error UaVirBASE is intended to support reproducible research and development in acoustic-based SSL, UAV surveillance, and intelligent sensing systems. This dataset fills a gap in the literature by offering a standardized benchmark specifically tailored to UAV audio-based localization tasks.Jekateryńczuk, G.; Szadkowski, R.; Piotrowski, Z. UaVirBASE: A Public-Access Unmanned Aerial Vehicle Sound Source Localization Dataset. Appl. Sci. 2025, 15, 5378. https://doi.org/10.3390/app15105378