Open AccessHigh‐order moment multi‐sensor fusion filter design of Markov jump linear systems
Author(s) -
Zhou Ziheng,
Luan Xiaoli,
He Shuping,
Liu Fei
Publication year - 2020
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
ISSN - 1751-9683
DOI - 10.1049/iet-spr.2020.0067
Subject(s) - moment (physics) , filter (signal processing) , gaussian , computer science , sensor fusion , markov process , algorithm , fusion , control theory (sociology) , mathematics , mathematical optimization , artificial intelligence , statistics , linguistics , physics , philosophy , control (management) , classical mechanics , quantum mechanics , computer vision
To solve the problem of high‐order moment Gaussian distribution (HGD) noise in state estimation, a fusion filter for Markov jump linear systems (MJLSs) with high‐order moment information obtained from sensor data is designed. To obtain high‐order moment information, the multi‐sensor MJLS is converted to a single‐mode system composed of high‐order moment components by using a cumulant generating function. Next, a filter design based on Bayesian theory is established to achieve state estimation with a high‐order moment information form according to the transformed single‐mode deterministic system. Subsequently, a high‐order moment fusion technique based on entropy theory is proposed to obtain a more accurate estimation result of the state by using the high‐order moment information obtained from various sensors. Comparing the first‐ and second‐order moment information obtained by traditional Gaussian distribution, the HGD introduces higher‐order moment information and makes the fusion process more reasonable. In this way, a more precise and reasonable performance of the state estimation is achieved, depending on the sensor fusion technique. To confirm the effectiveness and advantages of the proposed method, a numerical simulation example is provided with various fusion methods. Thus, the performance of the proposed fusion filter design is verified.