Open AccessResearch on Multi-satellite Observation Multi-region Task Planning based on Genetic Algorithm
Author(s) -
Ying Zhang,
Jianwei Wang,
Bo Yuan,
Chao Wang,
Lei Shi
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/685/1/012002
Subject(s) - spacecraft , computer science , satellite , situation awareness , genetic algorithm , scheduling (production processes) , aerospace , real time computing , task (project management) , systems engineering , earth observation satellite , earth observation , operations research , aerospace engineering , engineering , operations management , machine learning
Space-based resources play an important role in the observation and handling of emergency events, and are widely used in national economic activities. In recent years, the large increase in the number of orbital spacecraft and the strategic transformation of the aerospace equipment application model have made the practical task planning for multi-type satellites of practical significance. The research and application of space-based regional reconnaissance algorithms are of great significance for improving the comprehensive application efficiency of spacecraft, forming uniform coverage of key areas, and improving the uniformity of satellite resource utilization and situational awareness. Based on the actual background of engineering application, this paper describes the scheduling problem of Earth observation satellites. Under the constraints of satellite resource capability, observable time, conversion time between reconnaissance missions, energy, etc., a multi-satellite multi-target reconnaissance mission is established. Planning model. With the most resource-saving and high situational awareness uniformity as the optimization index, the optimized satellite reconnaissance mission planning scheme is obtained based on genetic algorithm.