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A fixed-lag smoothing algorithm for Markovian switching systems

机译:马尔可夫切换系统的固定滞后平滑算法

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A suboptimal approach to the fixed-lag smoothing problem for Markovian switching systems is presented. We augmented the system state and system model probability, so the fixed-lag smoothing problem is transformed to the filtering problem of a new augmented system. A new fixed-lag smoothing algorithm is developed by applying the basic structure of IMM, which is superior in MME methods, to the augmented systems. The algorithm is illustrated via two typical target tracking simulation examples, where a significant improvement over Chen's algorithm is achieved at the cost of a time delay.
机译:提出了解决马尔可夫切换系统固定滞后平滑问题的次优方法。我们增加了系统状态和系统模型概率,因此将固定滞后平滑问题转化为新的扩充系统的滤波问题。通过将在MME方法中优越的IMM基本结构应用于增强系统,开发了一种新的固定滞后平滑算法。通过两个典型的目标跟踪仿真示例说明了该算法,其中以时间延迟为代价,对Chen算法进行了重大改进。

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