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High-Order Interacting Multiple Model Filter Based on Mixture Transition Distribution

机译:基于混合转换分布的高阶交互多模型滤波器

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A novel nth-order interacting multiple model (IMMn) filter based on the mixture transition distribution (MTD) for maneuvering target tracking referred as IMMn-MTD filter is proposed here. It adopts MTD model rather than fully parameterized high-order Markov chain (MC) to approximate the model sequence transition probabilities. Since only a few independent parameters need to be fixed in MTD model, IMMn-MTD is more flexible compared with the high-order MC mothed. This approach simultaneously possesses the advantage in accuracy because high order model sequence is evaluated. Simulations are performed to demonstrate the effectiveness of the proposed approach.
机译:在此提出了一种基于用于操纵目标跟踪的混合转变分布(MTD)的新型NTH阶,用于操纵目标跟踪作为IMMN-MTD滤波器的混合转换分布。它采用MTD模型而不是完全参数化的高阶马尔可夫链(MC),以近似模型序列过渡概率。由于仅在MTD模型中需要修复一些独立的参数,因此与高阶MC相比,IMMN-MTD更灵活。这种方法同时具有精确度的优点,因为评估了高阶模型序列。进行模拟以证明所提出的方法的有效性。

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