Long-Range UAV Thermal Geo-Localization with Satellite Imagery
Long-Range UAV Thermal Geo-Localization with Satellite Imagery
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DOI：
10.1109/iros55552.2023.10342068
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
Jiuhong Xiao;Daniel Tortei;E. Roura;Giuseppe Loianno
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文献类型：
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作者：
Jiuhong Xiao;Daniel Tortei;E. Roura;Giuseppe Loianno
车载传感器，如相机和热传感器，已经成为全球定位系统(GPS)在无人机导航中进行地理定位的有效替代品。由于GPS可能会受到信号丢失和欺骗问题的影响，研究人员探索了基于相机的技术，如使用卫星RGB图像的视觉地理定位(VG)。此外，热地理定位(TG)已经成为无人机在低照度环境中进行远程飞行的关键。本文提出了一种新的基于卫星RGB图像的热地理定位框架，该框架包括多个域自适应方法，以解决热图像和卫星图像对可用性有限的问题。实验结果表明，即使在具有模糊自相似特征的热图像中，该方法也能获得可靠的热地理定位性能。我们根据无人机上收集的真实数据来评估我们的方法。我们还发布了代码和玻色子-夜间，这是一个配对的卫星热图像和未配对的卫星图像的数据集，用于与卫星图像的热地理定位。据我们所知，这项工作是首次提出了一种利用卫星RGB图像进行远程飞行的热地理定位方法。
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.