Conceptual Design of the FAST-D Formation Flying Spacecraft

Maessen, D.C.; Guo, Jian; Gill, Eberhard; Gunter, B. C.; Chu, Qi; Bakker, G.; Laan, E.; Moon, S.; Kruijff, Michiel; Zheng, Gangtie

doi:10.1007/978-3-642-03501-2_14

Cited by 3 publications

(3 citation statements)

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“…This hybrid Huber technique-based H-SDDF filtering algorithm is robust to deviations from the assumed Gaussian measurement distribution noise points, and this robustness mainly stems from the fact that the Ψ matrix and all residual values are not weighted equally [15][16]. That is, the larger residuals during the iteration process receive the weights of their absolute inverse.…”

Section: Robust Simplified Mean-difference Filtering Algorithm Based ...mentioning

confidence: 99%

Application of Robust Mean-Difference Filtering to Relative Navigation of Formation Spacecraft

Huang,

Gao

2024

Preprint

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This paper firstly introduces the basic knowledge required for relative navigation of formation spacecraft, which involves the description of the main coordinate systems, the modelling method of relative orbit dynamics of formation spacecraft, the introduction of common interstellar measurement models and the description of the measurement model of the measurement sensors, and then it is divided into two subsections to study the relative navigation problem of the formation spacecraft in two cases. Aiming at the problems of low filtering accuracy and slow convergence speed of the traditional extended Kalman filtering algorithm for formation spacecraft relative navigation, and considering the linear GPS measurement model, this paper simplifies and applies the standard mean difference filtering algorithm to spacecraft formation relative navigation. Simulation results show that the Simplified Divide Difference Filter (SDDF) proposed in this paper is suitable for the design of formation spacecraft relative navigation filters. In view of the non-Gaussian characteristics of the GPS measurement system in spacecraft formation flight, the Huber-based Divided Difference Filter (H-SDDF) algorithm is used to improve the robustness of the above SDDF algorithm, and is applied to the design of relative navigation filters for spacecraft formation flight, and the simulation results verify that the H-SDDF algorithm proposed in this paper is suitable for the design of relative navigation filters for spacecraft formation flight. The simulation results verify the effectiveness of the H-SDDF algorithm proposed in this paper. In summary, this paper focuses on the robust mean difference filter algorithm. The research includes the design of relative navigation filter algorithm for formation spacecraft and the full nonlinear state estimation problem when both the filter system and the measurement model are nonlinear. The main problems solved are: improving the filter estimation accuracy and enhancing the robustness of the filtering process. Finally, theoretical analyses and numerical simulations verify that the research done in this paper has a certain degree of improvement compared with the previous ones.

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Section: Robust Simplified Mean-difference Filtering Algorithm Based ...mentioning

confidence: 99%

Application of Robust Mean-Difference Filtering to Relative Navigation of Formation Spacecraft

Huang,

Gao

2024

Preprint

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“…This orbital geometry lends itself extremely well to perform synoptic and synergetic observations with the altimeters and especially the SPEX instruments on both spacecraft. The orbital geometry combined with the nine Earth looking fields of view (FOV) of the SPEX instrument [4] results in many simultaneous intersections of SPEX FOVs and in several overlapping SPEX FOVs at the Earth's surface, cf. Fig.…”

Section: Science Mode A2mentioning

confidence: 99%

“…This allows retrieval of aerosol characteristics at specific altitudes at a single moment in time and it allows making more observations of geolocations from various angles during a single pass (especially near the equator), which is highly desired for aerosol characterization. The ±5.7 km accuracy in the inter-satellite range is driven by the pixel size of SPEX at 650 km altitude, which is approximately 11.4 km [4].…”

Section: Science Mode A2mentioning

confidence: 99%

Mission Design of the Dutch-Chinese FAST Micro-Satellite Mission

Maessen

Guo

Gill

et al. 2009

Small Satellite Missions for Earth Observation

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The paper treats the mission design for the Dutch-Chinese FAST (Formation for Atmospheric Science and Technology demonstration) mission. The space segment of the 2.5 year mission consists out of two formation flying micro-satellites. During the mission, new technologies will be demonstrated and, using spectropolarimeter and altimeter payloads on both spacecraft, observations will be performed characterizing atmospheric aerosols and seasonal variations of height profiles in the cryosphere. The mission is divided into four phases, each with a different orbital geometry. The rationale for and the orbital geometry during these phases as well as the transitions between the phases are treated in detail. A major complication to the mission design is the amount of data that can be sent to the ground. Since only two moderately capable ground stations, one in Delft and one in Beijing, are baselined, as much data processing as possible has to be performed onboard to allow high duty factors for the science payloads. When this is not possible, alternative payload operation modes have to be sought with which maximum scientific data return can be obtained through as little payload operation as possible. Both options are dealt with in the paper.

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Relative Navigation

Horri

Palmer

2012

Distributed Space Missions for Earth System Monitoring

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Conceptual Design of the FAST-D Formation Flying Spacecraft

Cited by 3 publications

References 5 publications

Application of Robust Mean-Difference Filtering to Relative Navigation of Formation Spacecraft

Application of Robust Mean-Difference Filtering to Relative Navigation of Formation Spacecraft

Mission Design of the Dutch-Chinese FAST Micro-Satellite Mission

Relative Navigation

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