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。 Aiming at the fault detection of spacecraft downlink telemetry data, a corresponding non-stationary and anomalous component model is established. Based on the bounded influence of the regression coefficients of incremental sampling process, a new on-line detection algorithm for abrupt changes of spacecraft downlink data is proposed , The algorithm has a simple recurrence relationship and good fault tolerance. The experimental results show that this algorithm can effectively detect the spacecraft abnormal data and can overcome the adverse effects of the abnormal data and improve the reliability of the orbit spacecraft measurement and control process.