Research on optimization method of reconnaissance constellation based on multi-objective evolutionary algorithm

Abstract

In order to further solve the optimization problem of reconnaissance constellation and strengthen the construction of space-based reconnaissance system, the current optimization methods of reconnaissance constellation are studied and summarized. The design and optimization of reconnaissance constellation has the characteristics of multi-parameter, multi-objective, nonlinear and discontinuous, which is a typical multi-objective optimization problem. Multi-objective evolutionary algorithm is a kind of biological intelligence algorithm based on population, which carries out probabilistic search in decision space according to predetermined heuristic rules. It does not need continuity, differentiability and other conditions of the problem, and can get a group of solution sets close to Pareto frontier within a limited number of search times. It can effectively solve the multi-objective optimization problem and has been widely used in the multi-objective optimization of reconnaissance constellation. This paper discusses the construction of the reconnaissance constellation optimization model and the classification, advantages and disadvantages of the multi-objective evolutionary algorithm, discusses the application of the multi-objective evolutionary algorithm in the reconnaissance constellation optimization, and points out the development direction of the reconnaissance constellation optimization based on the multi-objective evolutionary algorithm.

Keywords

• constellation optimization|space-based reconnaissance|evolutionary algorithm|multi-objective optimization|many-objective optimization