Hierarchical distributed autonomous collaborative task planning system for intelligent remote sensing satellite

Abstract

The invention discloses a hierarchical distributed autonomous collaborative task planning system for an intelligent remote sensing satellite. The system comprises a multi-satellite task coordinator and an on-satellite scheduler, wherein the multi-satellite task coordinator distributes tasks in a task set to be distributed to multiple affiliated intelligent satellites and processes the tasks into meta-tasks which can be directly identified by the on-satellite scheduler; each intelligent satellite utilizes the on-satellite scheduler to carry out uniform scheduling on a new distributed task and an existing task; and before the multi-satellite task coordinator carries out task distribution, a scheduling result on the relevant on-satellite scheduler is estimated in advance and is taken as a basis for task distribution. Key scientific problems and technical problems of imaging task schedulability prediction, multi-task multi-resource dynamic scheduling under a high-dimensional space, refinedplanning and scheduling algorithm design are successfully tackled, a multi-satellite autonomous collaborative task planning technology can be better applied to the field of national defense construction, and the rationalization of a distribution scheme and the high efficiency of resource utilization can be accelerated.

Description

technical field [0001] The invention relates to the technical field of remote sensing satellites, in particular to a hierarchical distributed autonomous collaborative task planning system for intelligent remote sensing satellites. Background technique [0002] Remote sensing satellites are artificial satellites used as remote sensing platforms in outer space. Typically, remote sensing satellites remain in orbit for several years. Satellite orbits can be determined as needed. Remote sensing satellites can cover the entire earth or any designated area within a specified period of time. When running along a geosynchronous orbit, they can continuously remote sense a designated area on the earth's surface. All remote sensing satellites need remote sensing satellite ground stations. The satellite data obtained from the remote sensing market platform can monitor agriculture, forestry, ocean, land, environmental protection, meteorology, etc. Remote sensing satellites mainly includ...

AI Technical Summary

Problems solved by technology

[0004] (1) The complexity of the task planning problem

Intelligent satellite mission planning has certain particularities in four aspects: tasks, resources, constraints, and optimization objectives, and common resource scheduling models and optimization methods are difficult to solve

[0005] (2) The complexity and uncertainty of the scheduling algorithm

The randomness of the scheduling algorithm makes the scheduling results uncertain, and also increases the difficulty of schedulability prediction

[0006] (3) Complexity of task sample selection

[0007] (4) The complexity of sample feature extraction

How to select the features that have a decisive impact on the prediction process among various attributes is also very complicated

[0008] (5) The daily imaging observation requirements submitted by

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