Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise

Xiao Liang; Xiaojun Sun; David Tien; Wang Guanran

doi:10.1007/978-981-96-1758-6_59

Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise

Xiao Liang
, Xiaojun Sun
, David Tien
, Wang Guanran

Charles Sturt University

Heilongjiang University

Research output: Book chapter/Published conference paper › Conference paper › peer-review

Abstract

With the wide application of network data transmission, network control systems often encounter network attacks in the process of data transmission. In this paper, for a multi-sensor system with network attacks and longitudinal correlation noise, white multiplicity noise is used to describe the state of the system and uncer-tainty in the observation process. A set of random variables that follow Bernoulli distribution is selected to describe unknown network attacks in the data transmission process. When the observed data are lost, the current observed forecast value is used to compensate. For multi-sensor systems, a global optimal centralized Kalman filter is designed using linear unbiased minimum variance estimation criterion. Simulation results verify the effectiveness and feasibility of the algorithm.

Original language	English
Title of host publication	Proceedings of International Conference on Information Technology and Applications
Subtitle of host publication	ICITA 2024
Editors	Abrar Ullah, Sajid Anwar
Place of Publication	Singapore
Publisher	Springer
Pages	711-719
Number of pages	9
Volume	1248
ISBN (Electronic)	9789819617586
ISBN (Print)	9789819617579
DOIs	https://doi.org/10.1007/978-981-96-1758-6_59
Publication status	Published - 2025
Event	18th International Conference on Information Technology and Applications 2024: ICITA 2024 - Hilton Sydney, Sydney, Australia Duration: 17 Oct 2024 → 19 Oct 2024 https://2024.icita.world/#/ https://www.icita.world/files/ICITA_2024.pdf (Program)

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1248 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	18th International Conference on Information Technology and Applications 2024
Country/Territory	Australia
City	Sydney
Period	17/10/24 → 19/10/24
Internet address	https://2024.icita.world/#/ https://www.icita.world/files/ICITA_2024.pdf (Program)

Access to Document

10.1007/978-981-96-1758-6_59

Cite this

Liang, X., Sun, X., Tien, D., & Guanran, W. (2025). Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise. In A. Ullah, & S. Anwar (Eds.), Proceedings of International Conference on Information Technology and Applications: ICITA 2024 (Vol. 1248, pp. 711-719). (Lecture Notes in Networks and Systems; Vol. 1248 LNNS). Springer. https://doi.org/10.1007/978-981-96-1758-6_59

Liang, Xiao ; Sun, Xiaojun ; Tien, David et al. / Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise. Proceedings of International Conference on Information Technology and Applications: ICITA 2024. editor / Abrar Ullah ; Sajid Anwar. Vol. 1248 Singapore : Springer, 2025. pp. 711-719 (Lecture Notes in Networks and Systems).

@inproceedings{d73c727eff244fd68b753f4595a293dc,

title = "Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise",

abstract = "With the wide application of network data transmission, network control systems often encounter network attacks in the process of data transmission. In this paper, for a multi-sensor system with network attacks and longitudinal correlation noise, white multiplicity noise is used to describe the state of the system and uncer-tainty in the observation process. A set of random variables that follow Bernoulli distribution is selected to describe unknown network attacks in the data transmission process. When the observed data are lost, the current observed forecast value is used to compensate. For multi-sensor systems, a global optimal centralized Kalman filter is designed using linear unbiased minimum variance estimation criterion. Simulation results verify the effectiveness and feasibility of the algorithm.",

keywords = "Information fusion, Multi-sensor systems, Centralized Kalman filtering, Optimal filtering",

author = "Xiao Liang and Xiaojun Sun and David Tien and Wang Guanran",

year = "2025",

doi = "10.1007/978-981-96-1758-6\_59",

language = "English",

isbn = "9789819617579",

volume = "1248",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer",

pages = "711--719",

editor = "Abrar Ullah and Sajid Anwar",

booktitle = "Proceedings of International Conference on Information Technology and Applications",

address = "United States",

note = "18th International Conference on Information Technology and Applications 2024 : ICITA 2024 ; Conference date: 17-10-2024 Through 19-10-2024",

url = "https://2024.icita.world/\#/, https://www.icita.world/files/ICITA\_2024.pdf",

}

Liang, X, Sun, X, Tien, D & Guanran, W 2025, Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise. in A Ullah & S Anwar (eds), Proceedings of International Conference on Information Technology and Applications: ICITA 2024. vol. 1248, Lecture Notes in Networks and Systems, vol. 1248 LNNS, Springer, Singapore, pp. 711-719, 18th International Conference on Information Technology and Applications 2024, Sydney, New South Wales, Australia, 17/10/24. https://doi.org/10.1007/978-981-96-1758-6_59

Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise. / Liang, Xiao; Sun, Xiaojun; Tien, David et al.
Proceedings of International Conference on Information Technology and Applications: ICITA 2024. ed. / Abrar Ullah; Sajid Anwar. Vol. 1248 Singapore: Springer, 2025. p. 711-719 (Lecture Notes in Networks and Systems; Vol. 1248 LNNS).

Research output: Book chapter/Published conference paper › Conference paper › peer-review

TY - GEN

T1 - Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise

AU - Liang, Xiao

AU - Sun, Xiaojun

AU - Tien, David

AU - Guanran, Wang

PY - 2025

Y1 - 2025

N2 - With the wide application of network data transmission, network control systems often encounter network attacks in the process of data transmission. In this paper, for a multi-sensor system with network attacks and longitudinal correlation noise, white multiplicity noise is used to describe the state of the system and uncer-tainty in the observation process. A set of random variables that follow Bernoulli distribution is selected to describe unknown network attacks in the data transmission process. When the observed data are lost, the current observed forecast value is used to compensate. For multi-sensor systems, a global optimal centralized Kalman filter is designed using linear unbiased minimum variance estimation criterion. Simulation results verify the effectiveness and feasibility of the algorithm.

AB - With the wide application of network data transmission, network control systems often encounter network attacks in the process of data transmission. In this paper, for a multi-sensor system with network attacks and longitudinal correlation noise, white multiplicity noise is used to describe the state of the system and uncer-tainty in the observation process. A set of random variables that follow Bernoulli distribution is selected to describe unknown network attacks in the data transmission process. When the observed data are lost, the current observed forecast value is used to compensate. For multi-sensor systems, a global optimal centralized Kalman filter is designed using linear unbiased minimum variance estimation criterion. Simulation results verify the effectiveness and feasibility of the algorithm.

KW - Information fusion

KW - Multi-sensor systems

KW - Centralized Kalman filtering

KW - Optimal filtering

UR - https://rdcu.be/eCYjN

UR - https://www.scopus.com/pages/publications/105009400823

UR - https://www.scopus.com/pages/publications/105009400823#tab=citedBy

U2 - 10.1007/978-981-96-1758-6_59

DO - 10.1007/978-981-96-1758-6_59

M3 - Conference paper

SN - 9789819617579

VL - 1248

T3 - Lecture Notes in Networks and Systems

SP - 711

EP - 719

BT - Proceedings of International Conference on Information Technology and Applications

A2 - Ullah, Abrar

A2 - Anwar, Sajid

PB - Springer

CY - Singapore

T2 - 18th International Conference on Information Technology and Applications 2024

Y2 - 17 October 2024 through 19 October 2024

ER -

Liang X, Sun X, Tien D, Guanran W. Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise. In Ullah A, Anwar S, editors, Proceedings of International Conference on Information Technology and Applications: ICITA 2024. Vol. 1248. Singapore: Springer. 2025. p. 711-719. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-96-1758-6_59

Centralized fusion filter for multi-sensor systems with network attack and longitudinal correlation noise

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this