Efficient evaluation method for terminal entering state of Mars on the basis of intelligent learning

Abstract

The invention relates to an efficient evaluation method for the terminal entering state of Mars on the basis of intelligent learning, and belongs to the technical field of deep space exploration. A Mars entering trajectory optimization algorithm is used for optimizing maximum terminal height which can be reached by a spacecraft under different parameter combinations to provide the sample data of aprediction model based on Gaussian process regression. A genetic algorithm is used for the optimization solver of an entering trajectory under different scenes to avoid a local minimum value so as toguarantee the data quality of a Gaussian process training sample. A mean value function, a kernel function and a hyper-parameter are taken as the subject parameters of the Gaussian process and are selected as optimization parameters for describing correlation among samples so as to establish a Mars entering optimal terminal height prediction model based on the Gaussian process. By use of the method, the evaluation of the maximum terminal height under more than 3000 groups of different entering scenes can be finished in dozens of second orders, and an average relative error is within 4%.

Description

technical field [0001] The invention relates to an intelligent learning-based efficient evaluation method for the terminal state of Mars entry, in particular to an efficient evaluation method for the terminal state of the Mars entry stage based on Gaussian process regression (GPR), which belongs to the technical field of deep space exploration. Background technique [0002] Planetary exploration is one of the main fields in the development of deep space exploration technology. As the closest terrestrial planet in the solar system to Earth, Mars is usually the first choice for human planetary exploration. However, unlike the Earth environment, there are many challenges in entering the physical environment on Mars. The thin atmosphere and relatively high gravity make it difficult for the spacecraft to decelerate. When the spacecraft decelerates to the terminal height that can meet the requirements for starting the parachute or other deceleration devices, it will directly affe...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem of low solution efficiency in the prior art, and to provide an efficient evaluation method for Mars entry terminal state based on intelligent learning. A large number of evaluations have been made on the terminal altitude. For unmanned spacecraft and manned spacecraft, the impact of different entry speeds, terminal Mach numbers, lift-to-drag ratios, ballistic coefficients, and process constraints on the maximum terminal altitude that can be achieved by Mars entering the spacecraft is studied. Impact, use the evaluation results to analyze the characteristics of the Mars entry trajectory, so as to provide reference for the design of the Mars entry mission

Images