LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data
Knut Peterson, Zaid Mayers, Md Azmain Yousuf, Priontu Chowdhury, Solmaz Arezoomandan, Asher Julius Zaczepinski, Reihaneh Maarefdoust, David Han
AI summary
Problem
Existing drone detection datasets lack the scale, high resolution, long-range coverage, and multimodal data needed to train robust models for real-world aerial operations under varying weather, lighting, and backgrounds.
Approach
The authors collected and curated over 100,000 high-resolution RGB images and nearly 30,000 paired thermal images from drone-to-drone flights, sampling at 5 FPS to maximize environmental diversity and annotating precise drone range metadata.
Key results
- 102,532 high-resolution RGB images and 29,630 paired thermal images across diverse environments
- Comprehensive drone range annotations spanning 0 to 200 meters
- Balanced distribution of weather conditions and lighting scenarios for robust model training
- Open benchmark splits and dataset release to advance counter-drone research
Why it matters
It provides a critical, realistic benchmark for developing and evaluating robust drone detection systems needed for safe integration of UAVs into shared airspaces.
Abstract
Unmanned Aerial Vehicles (UAVs) have quickly become common in various airspaces, representing a wide range of applications from recreation flying to commercial photogra- phy and package delivery. With the increasing prevalence of UAVs, it becomes critical that both manned and unmanned aircraft can detect UAVs and other flying objects from long range to effectively track movement and ensure safe operation in shared spaces. While several datasets have been introduced for drone detection, the need for expanded high-quality data persists, especially in the area of high-resolution long-range drone data. To address this, we introduce a high-resolution dataset of 102,532 long-range RGB images of drones, sampled at 5 FPS from 128 distinct video clips taken mid flight during 17 different data collection days spread over 8 months to ensure a wide variety of lighting scenarios, flight locations, and background elements. The dataset boasts comprehensive drone range information across the dataset, as well as 29,630 IR images, all paired with RGB counterparts from the base dataset. As one of the first drone detection datasets to leverage 4K image resolution and paired 640x512 IR images, our work represents a significant advancement to enable the detection of drones at long range. For access to the complete dataset, please visit https://research.coe.drexel.edu/ece/imaple /lrddv3/.