Active Learning-Enhanced Dual Control for Angle-Only Initial Relative Orbit Determination
Active Learning-Enhanced Dual Control for Angle-Only Initial Relative Orbit Determination
Accurate relative orbit determination is a key challenge in modern space operations, particularly when relying on angle-only measurements. The inherent observability limitations of this approach make initial state estimation difficult, impacting mission safety and performance. This work explores the use of active learning (AL) techniques to enhance observability by dynamically designing the input excitation signal offline and at runtime. Our approach leverages AL to design the input signal dynamically, enhancing the observability of the system without requiring additional hardware or predefined maneuvers. We incorporate a dual control technique to ensure target tracking while maintaining observability. The proposed method is validated through numerical simulations, demonstrating its effectiveness in estimating the initial relative state of the chaser and target spacecrafts and its robustness to various initial relative distances and observation periods.
Kui Xie、Giovanni Romagnoli、Giordana Bucchioni、Alberto Bemporad
航空航天技术航天
Kui Xie,Giovanni Romagnoli,Giordana Bucchioni,Alberto Bemporad.Active Learning-Enhanced Dual Control for Angle-Only Initial Relative Orbit Determination[EB/OL].(2025-05-27)[2025-06-07].https://arxiv.org/abs/2505.21248.点此复制
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