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An Algorithm for Affordable Vision-Based GNSS-Denied Strapdown Celestial Navigation
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AI
DOI：10.3390/drones8110652.png)
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Celestial navigation is rarely seen in modern Uncrewed Aerial Vehicles (UAVs). The size and weight of a stabilized imaging system, and the lack of precision, tend to be at odds with the operational requirements of the aircraft. Nonetheless, celestial navigation is one of the few non-emissive modalities that enables global navigation over the ocean at night in Global Navigation Satellite System (GNSS) denied environments. This study demonstrates a modular, low cost, lightweight strapdown celestial navigation solution that is utilized in conjunction with Ardupilot running on a Cube Orange to produce position estimates to within 4 km. By performing an orbit through a full rotation of compass heading and averaging the position output, we demonstrate that the biases present in a strapdown imaging system can be nullified to drastically improve the position estimate. Furthermore, an iterative method is presented which enables the geometric alignment of the camera with the Attitude and Heading Reference System (AHRS) in-flight without an external position input. The algorithm is tested using real flight data captured from a fixed wing aircraft. The results from this study offer promise for the application of low cost celestial navigation as a redundant navigation modality in affordable, lightweight drones.
Keyword:
UAV
navigation
celestial
strapdown
stellar
orbital
modular
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D
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4.8
论文数:
3.9K
被引数:
8.3K
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