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CLC number: TP273
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2021-03-01
Cited: 0
Clicked: 6800
Citations: Bibtex RefMan EndNote GB/T7714
https://orcid.org/0000-0001-9303-9083
A novel multiple-outlier-robust Kalman filter
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Yulong HUANG, Mingming BAI, Yonggang ZHANG. A novel multiple-outlier-robust Kalman filter[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(3): 422-437.
@article{title="A novel multiple-outlier-robust Kalman filter",
author="Yulong HUANG, Mingming BAI, Yonggang ZHANG",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="23",
number="3",
pages="422-437",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000642"
}
%0 Journal Article
%T A novel multiple-outlier-robust Kalman filter
%A Yulong HUANG
%A Mingming BAI
%A Yonggang ZHANG
%J Frontiers of Information Technology & Electronic Engineering
%V 23
%N 3
%P 422-437
%@ 2095-9184
%D 2022
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000642
TY - JOUR
T1 - A novel multiple-outlier-robust Kalman filter
A1 - Yulong HUANG
A1 - Mingming BAI
A1 - Yonggang ZHANG
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 3
SP - 422
EP - 437
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000642
Abstract: This paper presents a novel multiple-outlier-robust Kalman filter (MORKF) for linear stochastic discrete-time systems. A new multiple statistical similarity measure is first proposed to evaluate the similarity between two random vectors from dimension to dimension. Then, the proposed MORKF is derived via maximizing a multiple statistical similarity measure based cost function. The MORKF guarantees the convergence of iterations in mild conditions, and the boundedness of the approximation errors is analyzed theoretically. The selection strategy for the similarity function and comparisons with existing robust methods are presented. Simulation results show the advantages of the proposed filter.
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