Peteris Racinskis, Janis Arents, Modris Greitans. (POSTER) Drone Detection and Localization using Low-Cost Microphone Arrays and Convolutional Neural Networks. 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) , 19(19), 80-82 pp. IEEE, 2023.
Bibtex citāts:
Bibtex citāts:
@inproceedings{14346_2023,
author = {Peteris Racinskis and Janis Arents and Modris Greitans},
title = {(POSTER) Drone Detection and Localization using Low-Cost Microphone Arrays and Convolutional Neural Networks},
journal = {2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) },
volume = {19},
issue = {19},
pages = {80-82},
publisher = {IEEE},
year = {2023}
}
author = {Peteris Racinskis and Janis Arents and Modris Greitans},
title = {(POSTER) Drone Detection and Localization using Low-Cost Microphone Arrays and Convolutional Neural Networks},
journal = {2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) },
volume = {19},
issue = {19},
pages = {80-82},
publisher = {IEEE},
year = {2023}
}
Anotācija: This paper examines the possibility of using low-cost commercial off-the-shelf audio recording equipment in combination with machine learning techniques to discover the presence of hostile UAVs. A convolutional neural network (CNN) was trained to detect and localize two types of quadrotor drones using ground truth position data collected with motion capture equipment. System performance was evaluated on pre-recorded validation data sets and in real-time operation. In both cases, drones can be successfully detected and localized within the constrained working volumes studied, achieving angular accuracies in the 8-13 deg range. However, further work remains to be done before system feasibility in outdoor conditions can be established.
Pilnais teksts: (POSTER) Drone Detection and Localization using Low-Cost Microphone Arrays and Convolutional Neural Networks