基于证据理论的航天器异常状态融合监测方法

利用多传感器数据对在轨航天器的状态进行监测时，多源信息具有的不确定性会导致通道间判定的不一致，目前工程上主要采用依靠专家经验进一步分析的方法，人工干预增加了判定结果的主观性，导致监测效率不高。本文针对此类问题提出了一种基于证据理论的融合方法，用以实现自动监测。设计了6种监测异常状态的信度函数，通过比较分析，最终选定根式函数，并根据数据特点进行了分段改进；结合工程需求介绍了参数设定原则。用此方法处理在轨航天器下传的多传感器数据，监测结果与现有人工判定结果相符，融合监测方法的有效性得以验证。

Anomaly State Monitoring for Spacecraft Based on Evidence Theory

During state monitoring for in-orbit spacecraft using multi-sensor data, uncertainty in multi-source information can cause inconsistent decisions among channels. The common engineering technical method to this problem is further analysed according to artificial expert expertise, which can add subjectivity to the decision result and cause low efficiency of monitoring. To realize automatic monitoring, a fusion method based on evidence theory is proposed for the monitoring problem. Six kinds of confidence function for anomaly state monitoring are designed. By comparison, the radical function is suitable. Improvement on subsection is made according to the data characteristics. Considering the engineering
requirements, principles setting adjustable parameters are introduced. This method is applied to deal with the downloaded multi-sensor data from in-orbit spacecraft. Monitoring result is consistent with the artificial conclusion. The effectiveness of this fusion monitoring method is verified.