@inproceedings{623603a69dd946bcb54463725d674be4,
title = "Autonomous detection, tracking, and geolocation for UAS-based situational awareness",
abstract = "Unmanned Aerial Systems (UAS) are increasingly used in both military and civilian applications for Intelligence, Surveillance, and Reconnaissance (ISR). Pairing UAS with AI enhances their utility by automating data collection and analysis, reducing operator workload and improving resilience to jamming. This enables autonomous ISR missions in contested environments and supports multi-drone coordination. We propose a processing chain using Convolutional Neural Networks for target detection and classification, followed by tracking, re-identification, and geolocation using data fusion and precision positioning methods. The system operates in near-real-time with a custom interface, including error propagation analysis to assess subsystem performance. A live demonstration was conducted using a fully open-source UAS platform.",
keywords = "Classification, Detection, Geolocation, Situational awareness, Tracking, UAV",
author = "A. Borghgraef and \{De Smet\}, T. and M. Vandewal",
note = "Publisher Copyright: {\textcopyright} 2025 SPIE. All rights reserved.; 11th Target and Background Signatures: Traditional Methods and Artificial Intelligence ; Conference date: 15-09-2025 Through 16-09-2025",
year = "2025",
month = oct,
day = "29",
doi = "10.1117/12.3069741",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "Society of Photo-Optical Instrumentation Engineers",
editor = "Karin Stein and Hogervorst, \{Maarten A.\}",
booktitle = "Target and Background Signatures XI",
}