  Onboard sensors, such as cameras and thermal sensors, have emerged as
effective alternatives to Global Positioning System (GPS) for geo-localization
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-localization (VG) using satellite RGB imagery. Additionally,
thermal geo-localization (TG) has become crucial for long-range UAV flights in
low-illumination environments. This paper proposes a novel thermal
geo-localization 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-localization
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 \textit{Boson-nighttime}, a dataset of paired satellite-thermal and
unpaired satellite images for thermal geo-localization with satellite imagery.
To the best of our knowledge, this work is the first to propose a thermal
geo-localization method using satellite RGB imagery in long-range flights.
