@article{SUN2026, 
author = {Qinbo SUN and Zhaohui DANG},
title = {Spacecraft guardian strategy design via motion-intent recognition},
year = {2026},
journal = {Acta Aeronautica et Astronautica Sinica},
volume = {47},
number = {S1},
keywords = {non-cooperative target, intent recogntion, deep learning, spacecraft guarding, orbital game},
url = {https://www.sciopen.com/article/10.7527/S1000-6893.2025.33013},
doi = {10.7527/S1000-6893.2025.33013},
abstract = {To address the challenges of unknown target intent and strategy selection under incomplete-information orbital games, an intent-inference-based maneuver-decision framework is proposed. First, considering the impulsive characteristics of spacecraft, a model-predictive-control scheme is devised within a finite-time horizon to rapidly generate guardian strategies for a single prespecified intent. Subsequently, an integrated guardian maneuver optimization method is developed that fuses intent interference results of a non-cooperative target, making it applicable to multi-intent scenarios. By dynamically adjusting the strategy optimization objective according to the inferred intent distribution, the escort maneuver strategy becomes more flexible when responding to uncertain operational environments. Simulation results across diverse space-guardian missions confirm the superior performance of the proposed approach.}
}