时序大数据流式计算处理在航天测控中心系统的应用  

Application of Time Series Big Data Based on Stream Computing in Space TT&C Center System

作　　者：符叶丹 张方圆 党琪 孙红梅 FU Yedan;ZHANG Fangyuan;DANG Qi;SUN Hongmei(College of Information System and Management,National University of Defense Technology,Changsha 410073,China;State Key Laboratory of Astronautic Dynamics,Xi’an 710043,China;不详)

机构地区：[1]国防科技大学系统工程学院,长沙710043 [2]宇航动力学国家重点实验室,西安710043

出　　处：《电讯技术》2023年第5期638-642,共5页Telecommunication Engineering

基　　金：装备军内科研项目(TJ20203C010083)。

摘　　要：大数据处理技术按照时效性可分为批处理与流处理两种模式。大量航天器工程测量数据经过测控设备的解码、译码等处理后形成原始数据发往测控中心,带有时间戳的这些原始数据、过程数据、处理结果数据及软件状态信息组成了时序大数据。通过对航天测控中心智能化决策模型的研究,设计了一种基于流式计算技术在航天测控中心系统的应用方法,指出了当前消息队列系统的瓶颈,并提出采用Kafka的消息通信机制来解决任务数量受限的问题。According to timeliness,big data processing technology can be divided into batch processing and stream processing.A large number of spacecraft engineering survey data is decoded and decoded by the TT&C equipment to form the original data and be sent to the TT&C center.These original data,process data,processing result data and software status information with time stamp constitute the time series big data.Through the research of intelligent decision-making model of space TT&C center,an application method based on flow computing technology in space TT&C center system is designed.The bottleneck of current message queue system is pointed out,and the message communication mechanism of Kafka is proposed to solve the problem of limited number of tasks.

关 键 词：航天测控中心 实时系统 流式计算 时序大数据 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]