摘要
针对航天器下行遥测数据故障检测问题,建立了相应的非平稳+异常分量模型,并借鉴采样数据新息增量过程的回归系数有界影响辨识方法,提出了航天器下行数据异常突变在线检测算法,该算法具有简捷的递推关系和良好的容错能力。实测数据结果表明,该算法可以有效地检测出航天器异常数据,并能克服异常数据的不利影响,提高在轨航天器测控过程的可靠性。
A non-stationary ＋ anomaly component model is established for online detection of spacecraft anomaly te- lemetry data. An online detection algorithm is presented for detection of spacecraft anomaly downlink data borrow- ing from the identification algorithm with bounded-influence for the coefficients of linear regression model during process of information increment of sampling data. Test results show that the algorithm effectively detects anomaly data of spacecraft, provides safeguard against the negative impact of anomaly data and thus increases the reliability of spacecraft TT＆C （Tracking, Telemetry and Command） processes.
出处
《飞行器测控学报》
CSCD
2013年第2期123-126,共4页
Journal of Spacecraft TT&C Technology
基金
国家自然科学基金项目(No.61074077)
关键词
航天器
下行遥测数据
故障检测
异常数据
检测算法
新息增量
spacecraft
downlink telemetry data
fault detection
anomaly data
detection algorithm
incremental information
