摘要
对于目标发生机动时的再入飞行器的跟踪问题,传统跟踪方法是采用机动模型的扩展卡尔曼滤波.本文在提高机动目标跟踪精度的探索中做了两方面的努力,一是在描述目标运动模型方面采用了更符合机动目标运动特性的多模型方法;另一方面,采用了隐含高阶精度的Unscented卡尔曼匹配滤波方法.对于交互多模型Unscented卡尔曼滤波器在仿真中易出现数值问题,给出了基于平方根滤波的数值鲁棒性的解决方法.
When tracking maneuvering reentry vehicles, an extended Kalman filter with maneuvering reentry vehicle （MaRV） model is usually used in a traditional method. To increase the performance of maneuvering target tracking two efforts are made. On the one hand, a more appropriate multiple model method is used in describing movement properties of the maneuvering target, on the other hand, the Unscented Kalman filter implying higher order precision is adopted in respective matching model. For numerical problems which are often encountered in implementing this interactive multiple model Unscented Kalman filter, a numerical robust solution is given by using square root filtering.
出处
《自动化学报》
EI
CSCD
北大核心
2007年第11期1220-1225,共6页
Acta Automatica Sinica
