On-board modeling of gravity fields of elongated asteroids using Hopfield neural networks

Zhao, Yunfeng; Yang, Hongwei; Li, Shuang; Zhou, Yue

doi:10.1007/s42064-022-0151-3

Cited by 9 publications

(2 citation statements)

References 23 publications

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“…Orbit uncertainty propagation (OUP) and orbit determination (OD) are essential in space missions such as near-Earth missions [1][2][3], asteroid exploration missions [4][5][6], lunar exploration missions [7], Venus exploration missions [8], and Jupiter exploration missions [9,10]. Among these space missions, deep space exploration missions rely on extremely accurate OUP and OD techniques.…”

Section: Introductionmentioning

confidence: 99%

Multivariate Attention-Based Orbit Uncertainty Propagation and Orbit Determination Method for Earth–Jupiter Transfer

Zhang,

Shi,

Han

2024

Applied Sciences

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Current orbit uncertainty propagation (OUP) and orbit determination (OD) methods suffer from drawbacks related to high computational burden, limiting their applications in deep space missions. To this end, this paper proposes a multivariate attention-based method for efficient OUP and OD of Earth–Jupiter transfer. First, a neural network-based OD framework is utilized, in which the orbit propagation process in a traditional unscented transform (UT) and unscented Kalman filter (UKF) is replaced by the neural network. Then, the sample structure of training the neural network for the Earth–Jupiter transfer is discussed and designed. In addition, a method for efficiently generating a large number of samples for the Earth–Jupiter transfer is presented. Next, a multivariate attention-based neural network (MANN) is designed for orbit propagation, which shows better capacity in terms of accuracy and generalization than the deep neural network. Finally, the proposed method is successfully applied to solve the OD problem in an Earth–Jupiter transfer. Simulations show that the proposed method can obtain a similar estimation to the UKF while saving more than 90% of the computational cost.

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Section: Introductionmentioning

confidence: 99%

Multivariate Attention-Based Orbit Uncertainty Propagation and Orbit Determination Method for Earth–Jupiter Transfer

Zhang,

Shi,

Han

2024

Applied Sciences

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“…Other studies have focused on the search for periodic orbits and on the study of liberation points in the vicinity of a rotating segment [11], [12]. Studies have been carried out on a model dealing with a straight segment linked to two masses at its extremities [13], [14] and which has been improved by an intelligent inversion method using Hopfield(HNN) neurons [15]. Our work consists first in modelling the asteroid by an inhomogeneous segment whose density profile is a fourth-order polynomial, then in establishing the analytical expression of the gravitational potential generated by this segment as a function of the density parameters.…”

Section: Introductionmentioning

confidence: 99%

Modelling the Dynamics of a Probe in Vicinity of Eross-433 With a Fourth-Order Polynomial Density Profile

ourabi,

Bennai

2023

Preprint

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In the present work, we study the motion of a probe in the gravitational field generated by an elongated geo-cruiser asteroid of irregular shape, which we model by an inhomogeneous mass distribution. We propose a model of inhomogeneous mass distribution with a symmetric polynomial density profile of order 4 and then establish the analytical expression of the gravitational potential generated by this segment. The Lagrangian formalism allowed us to establish the dynamic equations of motion of the probe in the gravitational field generated by this body, which we solved numerically.

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Fast generation of collision-free low-thrust trajectories for asteroid landing using deep neural networks

Hu,

Liu,

Yang

et al. 2024

Aerospace Science and Technology

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On-board modeling of gravity fields of elongated asteroids using Hopfield neural networks

Cited by 9 publications

References 23 publications

Multivariate Attention-Based Orbit Uncertainty Propagation and Orbit Determination Method for Earth–Jupiter Transfer

Multivariate Attention-Based Orbit Uncertainty Propagation and Orbit Determination Method for Earth–Jupiter Transfer

Modelling the Dynamics of a Probe in Vicinity of Eross-433 With a Fourth-Order Polynomial Density Profile

Fast generation of collision-free low-thrust trajectories for asteroid landing using deep neural networks

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