Analytical configuration uncertainty propagation of geocentric interferometric detection constellation

Dong, Qiao; Zhou, Xingyu; Li, Xiangyu

doi:10.1007/s42064-022-0157-x

Cited by 8 publications

(3 citation statements)

References 39 publications

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“…This poses a challenge to multi-constellation integrated navigation technology. In recent years, in order to increase the quantity of visible stars and select satellites with better geometric structures through satellite selection algorithms to indirectly improve navigation and positioning accuracy [60], major aerospace countries have successively developed from single-constellation systems to multi-constellation GNSS combined systems. This field includes research on satellite selection algorithms for multi-constellation integrated navigation and research on positioning solution methods for multi-constellation integrated navigation.…”

Section: Multi-constellation Gnss Lunar Satellite Orbit Determination...mentioning

confidence: 99%

Summary of Lunar Constellation Navigation and Orbit Determination Technology

Zhang,

Sun,

Chen

et al. 2024

Aerospace

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The Moon is the closest celestial body to the Earth. Its rich unique resources are an important supplement to the Earth’s resources and have a profound impact on the sustainable development of human society. As large-scale exploration missions gradually progress, demands for communication, navigation, surveying and other services of lunar-space probes have significantly increased. Constellation navigation and orbit determination technology will become an indispensable part of future lunar exploration infrastructure. This article systematically analyzes the current status of lunar relay navigation satellite networks at home and abroad, summarizes the technical principles of single-satellite and constellation navigation and orbit determination, discusses the technical difficulties in lunar navigation constellation orbit determination and navigation, and analyzes possible solutions. Finally, the development trend of research on high-precision orbit determination and navigation methods for lunar navigation constellations is proposed.

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Section: Multi-constellation Gnss Lunar Satellite Orbit Determination...mentioning

confidence: 99%

Summary of Lunar Constellation Navigation and Orbit Determination Technology

Zhang,

Sun,

Chen

et al. 2024

Aerospace

View full text Add to dashboard Cite

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“…Classic OUP methods include Monte Carlo simulation [23], unscented transform (UT) [24][25][26], cubature rule [27], state transition matrix [28,29], state transition tensor (STT) [30][31][32][33], and Gaussian mixture model (GMM) [34]. Park and Scheeres investigated the OUP problem of a spacecraft on a Sun-Earth L1 orbit [32,33].…”

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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“…In specific applications, solely predicting the nominal orbit is inadequate, as considering the evolution of uncertainty is also critical. This is particularly true in scenarios where mission reliability is of paramount concern, such as spacecraft constellation configuration [1,2], space rendezvous [3], and collision assessment [4].…”

Section: Introductionmentioning

confidence: 99%

Orbital Uncertainty Propagation Based on Adaptive Gaussian Mixture Model under Generalized Equinoctial Orbital Elements

Xie,

Xue,

et al. 2023

Remote Sensing

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The number of resident space objects (RSOs) has been steadily increasing over time, posing significant risks to the safe operation of on-orbit assets. The accurate prediction of potential collision events and implementation of effective and nonredundant avoidance maneuvers require the precise estimation of the orbit positions of objects of interest and propagation of their associated uncertainties. Previous research mainly focuses on striking a balance between accurate propagation and efficient computation. A recently proposed approach that integrates uncertainty propagation with different coordinate representations has the potential to achieve such a balance. This paper proposes combining the generalized equinoctial orbital elements (GEqOE) representation with an adaptive Gaussian mixture model (GMM) for uncertainty propagation. Specifically, we implement a reformulation for the orbital dynamics so that the underlying state and the moment feature of the GMM are propagated under the GEqOE coordinates. Starting from an initial Gaussian probability distribution function (PDF), the algorithm iteratively propagates the uncertainty distribution using a detection-splitting module. A differential entropy-based nonlinear detector and a splitting library are utilized to adjust the number of GMM components dynamically. Component splitting is triggered when a predefined threshold of differential entropy is violated, generating several GMM components. The final probability density function (PDF) is obtained by a weighted summation of the component distributions at the target time. Benefiting from the nonlinearity reduction caused by the GEqOE representation, the number of triggered events largely decreases, causing the necessary number of components to maintain uncertainty realism also to decrease, which enables the proposed approach to achieve good performance with much more efficiency. As demonstrated by the results of propagation in three scenarios with different degrees of complexity, compared with the Cartesian-based approach, the proposed approach achieves comparable accuracy to the Monte Carlo method while largely reducing the number of components generated during propagation. Our results confirm that a judicious choice of coordinate representation can significantly improve the performance of uncertainty propagation methods in terms of accuracy and computational efficiency.

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Analytical configuration uncertainty propagation of geocentric interferometric detection constellation

Cited by 8 publications

References 39 publications

Summary of Lunar Constellation Navigation and Orbit Determination Technology

Summary of Lunar Constellation Navigation and Orbit Determination Technology

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

Orbital Uncertainty Propagation Based on Adaptive Gaussian Mixture Model under Generalized Equinoctial Orbital Elements

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