Hao Yuan

Dr. Hao Yuan

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 August 2022 in Aerospace Science and Technology
Verified
Journal Article
Closed access
HYHao Yuan
Hao Yuan
DLDongxu Li
Dongxu Li

18 March 2024 in Acta Astronautica
Verified
Journal Article
Closed access
HYHao Yuan
Hao Yuan
DLDongxu Li
Dongxu Li
GHGuanwei He
Guanwei He
JWJie Wang
Jie Wang

11 October 2023 in Aerospace Science and Technology
Verified
Journal Article
Closed access
HYHao Yuan
Hao Yuan
DLDongxu Li
Dongxu Li
JWJie Wang
Jie Wang

21 September 2022 in Remote Sensing
Verified
Journal Article
Open access
PDF file
HYHao Yuan
Hao Yuan
DLDongxu Li
Dongxu Li
JWJie Wang
Jie Wang
The authors of this paper propose a robust star identification algorithm for a ‘Lost-In-Space’-mode star tracker for lost-cost CubeSat missions. A two-step identification framework and an embedded validation mechanism were designed to accelerate the process. In the first step, a masked distance map is designed to provide a shortlist of stars, and the embedded fast validation process enables the direct output of validated stars before the second step. In the second step, local similarity is utilized to select a set of stars from those shortlisted, and the final validation procedure rejects all unsatisfactory stars. This algorithm can provide reliable and robust recognition even when the captured star images include severe star positioning errors, missing stars and false stars. The proposed algorithm was verified by a simulation study under various conditions. As low-cost star sensors face harsh and unknown environments during deep space CubeSat missions such as asteroid exploration, the proposed algorithm with high robustness will provide an important function.

2 April 2024 in Nonlinear Dynamics
Verified
Journal Article
Closed access
PDF file
JWJie Wang
Jie Wang
QFQianyue Fu
Qianyue Fu
HYHao Yuan
Hao Yuan
HSHaibo Song
Haibo Song

26 April 2022 in Aerospace
Verified
Journal Article
Open access
PDF file
HYHao Yuan
Hao Yuan
DLDongxu Li
Dongxu Li
JWJie Wang
Jie Wang
This paper proposes a modified glideslope guidance method that optimizes a hybrid multiobjective of bearing-only navigation error and fuel consumption. The traditional glideslope guidance fixes uniform maneuver intervals and the initial approach velocity as a predetermined value, making this approach inflexible. In this paper, the maneuver intervals and the initial approach velocity were used as optimization variables, and a hybrid cost function was designed. The tradeoff between the two objectives was analyzed with a bearing-only navigation simulation conducted to reveal the navigation performance following different resulting trajectories. The result showed that the optimal scheduled times of maneuvers remained relatively stable under different tradeoff weights, while a strong correlation between the optimal initial approach velocity and the tradeoff weight was revealed. Therefore, when the optimization has to be solved several times online with different tradeoff weights, the initial approach velocity can be the only optimization variable, leaving the scheduled times of maneuvers fixed in the optimal values achieved offline. These findings provide a potential reference for far-approach trajectory design of bearing-only navigation.