IXV avionics architecture: Design, qualification and mission results

Succa, Massimo; Boscolo, I.; Drocco, A.; Malucchi, Giovanni; Dussy, Stephane

doi:10.1016/j.actaastro.2016.01.006

Acta Astronautica

2016

DOI: 10.1016/j.actaastro.2016.01.006

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IXV avionics architecture: Design, qualification and mission results

Massimo Succa

I. Boscolo

A. Drocco

et al.

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2022

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Research on real-time reachability evaluation for reentry vehicles based on fuzzy learning

Sun

et al. 2022

Open Astronomy

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Accurate and rapid prediction of reentry trajectory and landing point is the basis to ensure the reentry vehicle recovery and rescue, but it has high requirements for the continuity and stability of real-time monitoring and positioning data and the fidelity of the reentry prediction model. In order to solve the above contradiction, based on the theory of relative entropy and closeness in fuzzy learning, research on real-time evaluation of reentry reachability is presented in this article. With the Monte Carlo analysis data during the design and evaluation of the reentry vehicle control system, the reentry trajectory feature information base is designed. With the matching identification decision strategy between the identified trajectory and trajectory feature base, the reachability of the reentry vehicle, reachable trajectory, and landing point can be predicted. The simulation results show that by reasonably selecting the time window and using the evaluation method designed in this article, making statistics of the trajectory sequence number and frequency identified based on relative entropy and closeness method, the reachability evaluation results can be given stably, which is suitable for the real-time task evaluation of TT&C system.

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Research on real-time reachability evaluation for reentry vehicles based on fuzzy learning

Sun

et al. 2022

Open Astronomy

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Multi-Layer Fault-Tolerant Robust Filter for Integrated Navigation in Launch Inertial Coordinate System

et al. 2022

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As to an aerospace vehicle, the flight span is large and the flight environment is complex. More than that, the existing navigation algorithms cannot meet the needs to provide accurate navigation parameters for aerospace vehicles, which results in the decline of navigation accuracy. This paper proposes a multi-layer, fault-tolerant robust filtering algorithm of aerospace vehicle in the launch inertial coordinate system to address this problem. Firstly, the launch inertial coordinate system is used as the reference coordinate system for navigation calculation, and the state equation and measurement equation of the navigation system are established in this coordinate system to improve the modeling accuracy of the navigation system. On this basis, a multi-layer, fault-tolerant robust filtering algorithm is designed to estimate and compensate the unknown input in the state equation in real time and adjust the noise variance matrix in the measurement equation adaptively. Simulation results show that the errors about the integrated navigation system output parameters are reduced, through this algorithm, which improves the attitude, velocity and position estimation accuracy of the integrated navigation system. In addition, the algorithm enhances the fault tolerance and robustness of the filtering algorithm.

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IXV avionics architecture: Design, qualification and mission results

Cited by 2 publications

References 0 publications

Research on real-time reachability evaluation for reentry vehicles based on fuzzy learning

Research on real-time reachability evaluation for reentry vehicles based on fuzzy learning

Multi-Layer Fault-Tolerant Robust Filter for Integrated Navigation in Launch Inertial Coordinate System

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