系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (10): 2334-2339.doi: 10.3969/j.issn.1001-506X.2020.10.23

• 制导、导航与控制 • 上一篇    下一篇

基于高斯过程回归的大气进入段航天器飞行能力预测方法

王高岳(), 张慧君(), 陈贤(), 李昊()   

  1. 北京电子工程总体研究所, 北京 100854
  • 收稿日期:2020-01-20 出版日期:2020-10-01 发布日期:2020-09-19
  • 作者简介:王高岳(1994-),男,助理工程师,硕士,主要研究方向为导航、制导与控制。E-mail:386970547@qq.com|张慧君(1985-),女,高级工程师,硕士,主要研究方向为导航、制导与控制。E-mail:542631767@qq.com|陈贤(1990-),男,工程师,博士,主要研究方向为导航技术。E-mail:xian@zju.edu.cn|李昊(1998-),男,助理工程师,本科,主要研究方向为导航、制导与控制。E-mail:1018638681@qq.com

Prediction method of spacecraft flight capability in atmospheric entry phase based on Gaussian process regression

Gaoyue WANG(), Huijun ZHANG(), Xian CHEN(), Hao LI()   

  1. Beijing Institute of Electronic System Engineering, Beijing 100854, China
  • Received:2020-01-20 Online:2020-10-01 Published:2020-09-19

摘要:

轨迹优化技术是目前大气进入段研究的关键技术之一,如何在大气进入动力学复杂、航天器设计参数各异以及进入过程多约束的条件下,对进入轨迹性能参数进行评估是轨迹设计研究的重要问题。对此,以二维落点走廊为表征的大气进入段最大飞行航程作为性能指标,针对传统轨迹优化方法求解计算量庞大的问题,提出了一种基于高斯过程回归(Gaussian process regression, GPR)的大气进入段航天器飞行能力快速预测方法,挖掘航天器进入初始轨迹参量与轨迹包络特征参量之间的映射关系,求解航天器最大航程时避免了复杂的动力学建模以及大规模的迭代寻优过程。利用所提方法对1 000余组不同进入场景的进入轨迹最大航程进行快速预测,将预测结果用于进入段航天器飞行能力评估,为解决大气进入领域相关工程问题提供参考。

关键词: 大气进入, 轨迹优化, 飞行能力, 高斯过程回归

Abstract:

Trajectory optimization technology is one of the key technologies in the study of atmospheric entry phase. How to evaluate the performance parameters of the entry trajectory under the conditions of complicated atmospheric entry dynamics, different spacecraft design parameters and multiple constraints of the entry process is an important problem in the study of trajectory design. Thus, the maximum flight range of the atmospheric entry phase represented by the two-dimensional landing point corridor is taken as the performance index. Aiming at the problem that the traditional trajectory optimization method has a large amount of calculation, a fast prediction method of the flight capacity of the atmospheric entry phase based on the Gaussian process regression (GPR) is proposed to mine the mapping relationship between the initial trajectory parameters of the spacecraft and the characteristic parameters of the trajectory envelope. The method avoids complex dynamic modeling and large-scale iterative optimization process when solving the maximum range of spacecraft. By using the proposed method, the maximum range of entry trajectory of more than 1 000 groups of different entry scenarios is predicted rapidly, and the predicted results are used to evaluate the flight ability of entry spacecraft, thus providing reference for solving the engineering problems related to atmospheric entry.

Key words: atmospheric entry, trajectory optimization, flight capability, Gaussian process regression (GPR)

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