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Fuzzy Interacting Multiple Model H∞ Particle Filter Algorithm Based on Current Statistical Model

机译:基于当前统计模型的模糊交互多模型H∞粒子滤波算法

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摘要

In this paper, fuzzy theory and interacting multiple model are introduced into H infinity filter-based particle filter to propose a new fuzzy interacting multiple model H infinity particle filter based on current statistical model. Each model uses H infinity particle filter algorithm for filtering, in which the current statistical model can describe the maneuver of target accurately and H infinity filter can deal with the nonlinear system effectively. Aiming at the problem of large amount of probability calculation in interacting multiple model by using combination calculation method, our approach calculates each model matching probability through the fuzzy theory, which can not only reduce the calculation amount, but also improve the state estimation accuracy to some extent. The simulation results show that the proposed algorithm can be more accurate and robust to track maneuvering target.
机译:本文将模糊理论和相互作用多元模型引入基于H无限滤波器的粒子滤波器,提出了一种基于当前统计模型的新型模糊相互作用多重模型H无限粒子滤波器。每个模型都使用H无限粒子滤波算法进行滤波,当前的统计模型可以准确地描述目标的机动,H无限滤波器可以有效地处理非线性系统。针对组合模型计算中多个模型交互时概率计算量大的问题,该方法通过模糊理论对各个模型的匹配概率进行计算,不仅可以减少计算量,而且可以将状态估计的精度提高到一定程度。程度。仿真结果表明,该算法可以更准确,鲁棒地跟踪机动目标。

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