Time-Varying Directional State Transition Tensor for Orbit Uncertainty Propagation

The directional state transition tensor (DSTT) reduces the complexity of the state transition tensor (STT) by aligning the STT terms in sensitive directions only, which provides comparable accuracy in orbital uncertainty propagation. The DSTT assumes the sensitive directions to be constant during the integration and only works at a predefined epoch. This paper proposes a time-varying DSTT (TDSTT) to improve the DSTT. The proposed TDSTT computes the sensitive directions with time; thereby, it can perform uncertainty propagation analysis at any point instead of only a predefined epoch as the DSTT does. First, the derivatives of the sensitive directions are derived. Then, the differential equations for the high-order TDSTTs are derived and simplified using the orthogonality of sensitive directions. Next, complexity analysis is implemented to show the advantages of the proposed TDSTT over the STT. Finally, the TDSTT is applied to solve orbital uncertainty propagation problems in highly nonlinear three-body systems. Numerical results show that the proposed TDSTT can yield nearly the same level of accuracy as the STT and DSTT. It is approximately 94% faster than the STT, and when investigating the evolutions of orbital uncertainties, it can have a computational advantage over the DSTT.

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Publication Details

Journal
Journal of Guidance Control and Dynamics
Published
2026-02-05
DOI
https://doi.org/10.2514/1.g009000
Primary Topic
Tensor decomposition and applications
Type
article
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article

Time-Varying Directional State Transition Tensor for Orbit Uncertainty Propagation

Roberto Armellin, Qiao Dong, Xingyu Zhou, Xiangyu Li
Journal of Guidance Control and Dynamics
Tensor decomposition and applications
article

Time-Varying Directional State Transition Tensor for Orbit Uncertainty Propagation

Roberto Armellin, Qiao Dong, Xingyu Zhou, Xiangyu Li
article en

Abstract

The directional state transition tensor (DSTT) reduces the complexity of the state transition tensor (STT) by aligning the STT terms in sensitive directions only, which provides comparable accuracy in orbital uncertainty propagation. The DSTT assumes the sensitive directions to be constant during the integration and only works at a predefined epoch. This paper proposes a time-varying DSTT (TDSTT) to improve the DSTT. The proposed TDSTT computes the sensitive directions with time; thereby, it can perform uncertainty propagation analysis at any point instead of only a predefined epoch as the DSTT does. First, the derivatives of the sensitive directions are derived. Then, the differential equations for the high-order TDSTTs are derived and simplified using the orthogonality of sensitive directions. Next, complexity analysis is implemented to show the advantages of the proposed TDSTT over the STT. Finally, the TDSTT is applied to solve orbital uncertainty propagation problems in highly nonlinear three-body systems. Numerical results show that the proposed TDSTT can yield nearly the same level of accuracy as the STT and DSTT. It is approximately 94% faster than the STT, and when investigating the evolutions of orbital uncertainties, it can have a computational advantage over the DSTT.

Journal of Guidance Control and DynamicsVol. 49(3)
Beijing Institute of Technology (CN), University of Auckland (NZ)
Openalex Percentile: Top 66%
Tensor decomposition and applications
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Time-Varying Directional State Transition Tensor for Orbit Uncertainty Propagation — Roberto Armellin, Qiao Dong, et al. · Journal of Guidance Control and Dynamics (2026) | TGRS Research Map | TGRS