Long-Range UAV Thermal Geo-Localization with Satellite Imagery

Jiuhong Xiao, Daniel Tortei, Eloy Roura, Giuseppe Loianno

Abstract: Onboard sensors, such as cameras and thermal sensors, have emerged as effective alternatives to Global Positioning System (GPS) for geo-Iocalization in Unmanned Aerial Vehicle (UAV) navigation. Since GPS can suffer from signal loss and spoofing problems, researchers have explored camera-based techniques such as Visual Geo-Iocalization (VG) using satellite RGB imagery. Additionally, thermal geo-Iocalization (TG) has become crucial for long-range UAV flights in low-illumination environments. This paper proposes a novel thermal geo-Iocalization framework using satellite RGB imagery, which includes multiple domain adaptation methods to address the limited availability of paired thermal and satellite images. The experimental results demonstrate the effectiveness of the proposed approach in achieving reliable thermal geo-Iocalization performance, even in thermal images with indistinct self-similar features. We evaluate our approach on real data collected onboard a UAV. We also release the code and Boson-nighttime, a dataset of paired satellite-thermal and unpaired satellite images for thermal geo-Iocalization with satellite imagery. To the best of our knowledge, this work is the first to propose a thermal geo-Iocalization method using satellite RGB imagery in long-range flights.