Visual navigation is a commonly researched alternative to the use of global navigation satellite systems in challenging environments where satellite signals are not available. However, the vast majority of visual navigation techniques studied to date require scene illumination of some form. In this study, we use a low-resolution long-wave infrared (LWIR) image sensor sensitive to thermal emissivity within an optical flow processing engine to extend a low complexity track-based navigation scheme for fixed wing aircraft to operate at night. A mixture of closed and open loop flight experiments conducted on a small UAV integrated with the new sensor demonstrate: accurate track-based navigation in visual darkness; that the LWIR sensor performs equivalently to the benchmark optical flow sensor during daylight and continues to operate in low light; and that the LWIR sensor is able to detect suitable textures for operation at night across a wide span of altitudes. These results demonstrate utility of optical flow algorithms with low-resolution thermal scenes as a novel aircraft navigation sensor for day and night operation.

中文翻译：

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使用长波长红外的低复杂度视觉无人机航迹导航

视觉导航是在卫星信号不可用的挑战性环境中使用全球导航卫星系统的一种普遍研究的替代方法。然而，迄今为止研究的绝大多数视觉导航技术都需要某种形式的场景照明。在这项研究中，我们在光流处理引擎中使用对热发射率敏感的低分辨率长波红外 (LWIR) 图像传感器来扩展低复杂性的基于轨道的导航方案，以便固定翼飞机在夜间运行。在与新传感器集成的小型无人机上进行的闭环和开环飞行实验的混合证明：在视觉黑暗中准确的基于轨道的导航；LWIR 传感器在日光下的性能与基准光流传感器相当，并在低光下继续工作；并且 LWIR 传感器能够检测到适合夜间操作的纹理，跨越大跨度的高度。这些结果证明了具有低分辨率热场景的光流算法作为一种适用于白天和夜间操作的新型飞机导航传感器的实用性。