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

delete2019-07-01
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PRE
AI
Q
Qicong Wang *
X
Xiaoqiang Chen
L
Lin Zhang
金丽 cover
金丽 (Jin Li)
C
Chong Zhao
M
Man Qi
DOI:10.1007/s40815-019-00678-ydelete
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Abstract

Abstract

En 中文
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.
Keywords:
Fuzzy theory
Interacting multiple model
Particle filter
H infinity filter
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Journal

International Journal of Fuzzy Systems cover
International Journal of Fuzzy Systems
IF:
3.6
Papers:
2.2K
Citations:
4.3K

Organization

C
Canterbury Christ Church University
Scholars:
801
Papers: 727
Citations: 812
X
xiamen university
Scholars:
5.8W
Papers: 3.7W
Citations: 67