Anomaly Detection for Spacecraft by Estimating Parameters with Particle Filter
Anomaly Detection for Spacecraft by Estimating Parameters with Particle Filter
复制标题
通过粒子滤波器估计参数进行航天器异常检测
DOI：
10.2322/jjsass.55.355
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
K. Machida
中科院分区：
文献类型：
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作者：
Kohei Goto;Y. Kawahara;T. Yairi;K. Machida
提出了一种同时估计航天器状态和参数的航天器早期异常检测方法。我们采用了扩展的粒子滤波算法，以估计不仅状态，而且参数。该方法将参数的人工进化和参数的核平滑结合到粒子滤波算法中。每个参数都与航天器各部件的状态有关，因此通过参数变化的标志可以了解航天器内发生的情况。我们测试了航天器姿态运动的模拟算法。
This paper proposes a method of early spacecraft anomaly detection by simultaneously estimating its states and parameters. We applied an extended particle filter algorithm in order to estimate not only states but also parameters. In this method, we incorporated artificial evolution of parameters and kernel smoothing of parameters into the ordinary particle filter algorithm. Each parameter is related to each state of the spacecraft components, so we can understand what is happening in the spacecraft by finding out parameters’ changing signs. We tested the algorithm on a simulation of spacecraft attitude motion.