Multi-satellite cooperative task planning method

Abstract

The invention provides a multi-satellite cooperative task planning method. The multi-satellite cooperative task planning method comprises the following steps: step 1, setting a coding rule for a multi-satellite cooperative task; 2, searching a suboptimal solution of the multi-satellite cooperative task by adopting an ant colony algorithm based on a coding rule; and step 3, when ant colony algorithm search falls into local optimum, using a suboptimal solution quickly searched by the ant colony algorithm as an initial solution of a simulated annealing algorithm, continuing to search by adoptingthe simulated annealing algorithm until an iterative step number is reached or an optimization target is reached, outputting a result, and determining an execution satellite corresponding to each task. The invention discloses a multi-satellite cooperative task planning method. A suboptimal solution quickly searched by an ant colony algorithm is used as an initial solution of a simulated annealingalgorithm; the simulated annealing algorithm can start to optimize the problem at a high starting point, the defects that the search speed in the early stage of simulated annealing is low and the antcolony algorithm is prone to falling into the optimum are overcome, the optimization speed is increased, meanwhile, a better solution can be found, and task planning is better.

Description

technical field [0001] The invention belongs to the technical field of deep space exploration, and relates to a satellite task planning method, in particular to a multi-satellite coordinated task planning method. Background technique [0002] Earth Observing Satellite (EOS) mainly obtains relevant information on the earth's surface from space through space-borne sensors, and has unique advantages such as long operating time and wide coverage. At present, earth observation satellites have played an important role in many fields such as disaster prevention and control, weather forecasting, environmental protection, military reconnaissance, modern agriculture, and land surveying and mapping, and have brought considerable social and economic benefits to mankind. At present, the rapid development of the field of earth observation has brought unprecedented opportunities and challenges. Users are increasingly dependent on remote sensing information, which makes the observation targ...

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Problems solved by technology

[0005] In order to overcome the deficiencies of the existing technology, the inventors have carried out dedicated research and proposed a multi-satellite cooperative mission planning method combining ant colony algorithm and simulated annealing algorithm. The ant colony algorithm has a fast search speed in the early stage but is prone to premature stagnation state, the simulated annealing algorithm has a strong local search ability but the early search speed is slow, etc., the planning method of the present invention first uses the ant colony algorithm to perform a fast search, and when it falls into a local optimum, the simulated annealing algorithm is used for global optimization. Ensure that the algorithm has fast convergence and global search capabilities, has the advantages of fast search speed in the early stage, and can jump out of local optimum in the later stage of search, thus completing the present invention

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