深空探测学报（中英文）2025，Vol.12Issue(2)：162-171,10.DOI:10.15982/j.issn.2096-9287.2025.20240048
QLEKF的木星探测环绕段自主导航方法
Research on an Autonomous Navigation Method for the Orbital Phase of Jupiter Probe Based on QLEKF
摘要
Abstract
To address the challenge of noise uncertainty affecting filtering performance in Jupiter's complex environment,an optical autonomous navigation scheme was established based on the relative line-of-sight information from multiple Jovian moons,using a simplified QLEKF(Q-Learning Extended Kalman Filter)algorithm with a single filter to estimate the position and velocity of the probe.The QLEKF-single(Single Filter Q-learning Extended Kalman Filter)designs a reward function based on the innovation of a single EKF filter.The Q-learning algorithm adaptively selected the values of the noise covariance matrix,while the SoftMax strategy was employed for action selection,ultimately achieving iterative system state estimation by EKF filter.Through simulation by randomly generating initial state estimates and measurement noise,the simplified model of Jupiter's real orbital dynamics was verified.It demonstrated that in scenarios with noise uncertainty,the QLEKF-single algorithm effectively improved navigation accuracy compared to traditional filtering methods.Moreover,compared to the QLEKF algorithm,the run time was reduced by more than 10%with little change in accuracy.关键词
自主导航/QLEKF/贪婪算法/SoftMax算法/木星环绕Key words
autonomous navigation/QLEKF/greedy algorithm/SoftMax algorithm/Jupiter orbit分类
航空航天引用本文复制引用
戴志雯,侯博文,张艺捷,何章鸣,陆丹丹..QLEKF的木星探测环绕段自主导航方法[J].深空探测学报（中英文）,2025,12(2):162-171,10.基金项目
国家重点研发计划(2020YFA0713502) （2020YFA0713502）
