摘要
日益增多的空间目标对近地轨道环境下的空间活动构成严重威胁。空间环境态势感知技术对于监测空间目标、评估空间事件、保障在轨安全至关重要。AI应用于空间态势感知具有独特优势,体现在对传感数据的分析、挖掘能力,对复杂多变的空间环境要素的自学习与迁移能力,以及整合先验知识和现有数据实现决策与预判能力。本文概述了AI在空间环境态势感知领域的研究进展,包括数据、感知、决策三个维度。针对空间数据的特点和空间态势感知系统面临的新挑战,提出将分布式机器学习、多智能体等AI新兴技术应用于数据共享、协同监测的新思路。
The increasing amount of space objects poses a severe threat to space activities in near-Earth orbits.Space situational awareness technology is crucial for monitoring space objects,assessing space events,and ensuring on-orbit safety.The application of AI in space situational awareness offers unique advantages,manifested in its analytical and mining capabilities for sensor data,its self-learning and transferability capabilities in the face of complex and dynamic space environmental factors,as well as its ability to integrate prior knowledge and existing data for decision-making and prediction.This article provides an overview of AI research progress in the field of space situational awareness,encompassing three dimensions:data,perception,and decision-making.To address the characteristics of space data and the new challenges faced by space situational awareness systems,new approaches involving emerging AI technologies such as distributed machine learning and multi-agent systems for data sharing and collaborative monitoring are proposed.
作者
侯鹏荣
王哲龙
武强
仇森
褚庆浩
曾梓康
HOU Peng-rong;WANG Zhe-long;WU Qiang;QIU SenCHU Qing-hao;ZENG Zi-kang(Dalian University of Technology,Dalian 116024,China;Beijing Institute of Satellite Environmental Engineering,Beijing 100000,China)
出处
《空间碎片研究》
CSCD
2023年第4期11-21,共11页
Space Debris Research
基金
科技创新2030——“新一代人工智能”重大项目(2022ZD0117302)。
关键词
空间目标
近地轨道
态势感知
人工智能
数据共享
space objects
near-Earth orbits
situational awareness
artificial intelligence
data sharing
