AI 中文总结
研究针对深空导航联合航天器姿态-轨道估计及双星跟踪器对准校准问题，提出全乘法无迹卡尔曼滤波器，通过融合多种测量并保留天体像差，对比乘法扩展卡尔曼滤波器，蒙特卡罗结果显示其在粗传播间隔时性能更优。
AI 中文摘要
本文开发了一种几何一致的全乘法无迹卡尔曼滤波器（FM-UKF），用于联合航天器姿态-轨道估计以及同时进行双星跟踪器对准校准。该估计器使用21维局部误差状态，结合姿态、角速度、陀螺仪偏差、惯性位置和速度，以及在混合四元数-欧几里得流形上的两个跟踪器对准向量。融合了陀螺仪、星跟踪器和行星视线测量，保留了天体像差以捕获与速度相关的光学耦合。使用相同的标称状态、姿态收缩和单位向量测量几何，将乘法扩展卡尔曼滤波器（MEKF）作为一阶基线实现。蒙特卡罗结果表明，短步性能相似，但在粗传播间隔时，所提出的FM-UKF保持一致，而MEKF出现发散。
英文摘要
This paper develops a geometry-consistent fully multiplicative unscented Kalman filter (FM-UKF) for joint spacecraft attitude--orbit estimation with simultaneous dual star-tracker misalignment calibration. The estimator uses a 21-dimensional local error state combining attitude, angular velocity, gyroscope bias, inertial position and velocity, and two tracker-misalignment vectors on a mixed quaternion--Euclidean manifold. Gyroscope, star-tracker, and planet line-of-sight measurements are fused, with celestial aberration retained to capture velocity-dependent optical coupling. A multiplicative extended Kalman filter (MEKF) is implemented as a first-order baseline using the same nominal state, attitude retraction, and unit-vector measurement geometry. Monte Carlo results show similar short-step performance, while at coarse propagation intervals the proposed FM-UKF remains consistent and the MEKF exhibits divergence.
Comments21 pages, 13 figures
