Task observation plan solution method and system based on genetic algorithm for multiple agile satellites

Abstract

The invention relates to a task observation plan solution method and system based on a genetic algorithm for multiple agile satellites. The method and system can support task planning of the agile satellites, and a target function and a constraint analysis model are constructed according to the features of the agile satellites; by figuring out a solution to the constructed constraint analysis model satisfying task planning, selection, overlapping and variation of genetic searching algorithms are conducted to achieve conflict between every two adjacent tasks, an observation planning scheme is optimized, an optimal observation plan satisfying constraint conditions is generated, the resource utilization rate of the satellites is improved, and a timeliness problem during task execution of theagile satellites is solved. For different task conditions, different disposal methods are selected to achieve reasonable distribution of satellite resources, the quantity of single-track observation tasks is increased, and the response timeliness is improved.

Description

technical field [0001] The invention relates to a method and system for solving an agile multi-satellite mission observation plan based on a genetic algorithm, and belongs to the technical field of satellite observation mission planning. Background technique [0002] In non-agile satellite imaging mission planning, only the satellite's side-view imaging capability is considered, and scholars at home and abroad have made very in-depth research on this. Established related models including point targets, regional targets, moving targets, off-orbit stereo imaging and multi-satellite planning, and preliminarily realized the task composite observation between non-agile satellites for earth observation point targets. At the same time, different algorithms have been established for different models, the advantages and disadvantages of corresponding algorithms have been analyzed, and new composite algorithms have been compared and developed, with many achievements. [0003] At pres...

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Problems solved by technology

Guo Hao et al. studied the calculation of the roll angle of the smart satellite remote sensor and clustered the intensive tasks of the agile imaging satellite, and designed a clustering algorithm based on the max-min ant system, but there are agile The disadvantages of low resource efficiency and poor timeliness in satellite mission planning

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