Abstract
Relative navigation of multiple spacecraft based on the processing of Global Navigation Satellite System (GNSS) signals has been successfully performed in Low Earth Orbit (LEO). An accuracy on the order of one millimeter for relative positioning can be achieved in post-processing by using Carrier Phase Differential GNSS (CDGNSS) and recovering the correct carrier phase integer ambiguity. However, the real-time performance and accuracy without post100761-processing can be much lower because of limited on-board computational resources, signal obstruction, multipath interference induced by other spacecraft orbiting in proximity, and inaccurate knowledge of the spacecraft’s attitude. The navigation accuracy can be considerably degraded in higher Earth orbits above the GNSS constellation because of weaker signals and poor Geometric Dilution of Precision (GDOP). On the other hand, spacecraft navigation based on monocular vision is typically not as accurate as the one based on CDGNSS. In this paper, we review a novel multi-sensor navigation approach that utilizes a tight fusion of carrier phase GNSS observations and monocular measurements which enables fast and robust autonomous relative pose estimation of cooperative spacecraft in a degraded GNSS environment. We consider significant tracking noise and high operation orbits above the GNSS constellation characterized by weaker signals, lower visibility, higher GDOP, and low GNSS visibility. The architecture and algorithms are evaluated using both simulated Geosynchronous Earth Orbit data and real GPS data collected in an urban environment, thereby demonstrating that fusing GNSS with vision can provide better accuracy, robustness, and faster GNSS integer ambiguity resolution than when using GNSS only, especially in degraded GNSS conditions.
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