2020
DOI: 10.1016/j.icarus.2019.113574
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Improving Hayabusa2 trajectory by combining LIDAR data and a shape model

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Cited by 17 publications
(34 citation statements)
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“…However, for the current analysis of data from mid-altitude operation (see subsection Selected data and comparison method), we utilized another image-based trajectory also provided by the engineering team during this special science observation period. Although the image-based trajectory was better than the HPK trajectory and the same method as Matsumoto et al (2020) was applied in this study, the resultant footprint position may be less accurate than that in Matsumoto et al (2020). This is because the method relies on along-track topographic information, i.e., it is difficult to retain a sufficiently long unperturbed arc due to more frequent thrusting to maintain the spacecraft altitude between 5.1 and 5.2 km.…”
Section: Lidarmentioning
confidence: 97%
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“…However, for the current analysis of data from mid-altitude operation (see subsection Selected data and comparison method), we utilized another image-based trajectory also provided by the engineering team during this special science observation period. Although the image-based trajectory was better than the HPK trajectory and the same method as Matsumoto et al (2020) was applied in this study, the resultant footprint position may be less accurate than that in Matsumoto et al (2020). This is because the method relies on along-track topographic information, i.e., it is difficult to retain a sufficiently long unperturbed arc due to more frequent thrusting to maintain the spacecraft altitude between 5.1 and 5.2 km.…”
Section: Lidarmentioning
confidence: 97%
“…This was carried out after estimating the spacecraft trajectory using the LIDAR measurements. We adjusted spacecraft positions such that convex or concave topographic features contained in the LIDAR tracks were fit to the existing global shape model (Matsumoto et al 2020). The correction term with respect to the given initial trajectory was expressed by a polynomial function of time, and we searched for the best correction that minimized the discrepancy using the Markov chain Monte Carlo (MCMC) method.…”
Section: Lidarmentioning
confidence: 99%
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