Collaboration between multiple super-agile satellites with dynamic imaging capabilities provides an opportunity for highly efficient observation of large-area targets. Reasonable allocation of multi-satellite resources and determination of the action sequences of each satellite are two key requirements for multiple super-agile satellite mission planning. We propose a multi-satellite collaborative mission planning approach for an area target imaging mission, considering the dynamic imaging characteristics, achieving integrated optimization of the allocation of multi-satellite resources and determination of the action sequences of each satellite. A multi-satellite mission planning model with two objectives was established, with the objective functions being to maximize the observation coverage revenue and minimize the task performance time. An improved particle swarm optimization algorithm, represented by introducing particle learning/selection strategies and variable type-adaptive position updating methods, addresses the discrete–continuous hybrid variables in this optimization model. The proposed method was verified by constructing three groups of comparative experiments with area targets of different sizes. The proposed method showed consistent adaptability to various complexities and achieved synchronous optimization of the allocation of multi-satellite resources and determination of the action sequence of each satellite in areas of different sizes. Compared with existing algorithms, the proposed algorithm obtained superior imaging mission schemes with lower computational consumption, higher observation coverage revenues, or shorter task performance time. The experimental results showed that the proposed multi-satellite collaborative mission planning approach could be used to the ground operational systems of super-agile satellite constellations.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Multiple super-agile satellite collaborative mission planning for area target imaging


    Beteiligte:
    Zezhong LU (Autor:in) / Xin Shen (Autor:in) / Deren LI (Autor:in) / Dilong Li (Autor:in) / Yaxin Chen (Autor:in) / Di Wang (Autor:in) / Shuai Shen (Autor:in)


    Erscheinungsdatum :

    2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Energy-Dependent Mission Planning for Agile Earth Observation Satellite

    Zhao, Lin / Wang, Shuo / Hao, Yong et al. | ASCE | 2018


    The Mission Planning System for AGILE Mission

    Del Bello, Giovanni / Michetti, Antonio / D'Amico, Fabio | AIAA | 2006


    The Reference Activity Plan: Collaborative, Agile Planning for NASA’s Europa Clipper Mission

    Schimmels, Kathryn / Bindschadler, Duane / Ferguson, Eric et al. | NTRS | 2020


    The Reference Activity Plan: Collaborative, Agile Planning for NASA's Europa Clipper Mission

    Schimmels, Kathy / Bindschadler, Duane / Ferguson, Eric et al. | NTRS | 2020


    The Reference Activity Plan: Collaborative, Agile Planning for NASA's Europa Clipper Mission

    Pinover, Kaley / Ferguson, Eric / Bindschadler, Duane et al. | IEEE | 2020