Privacy-Preserving Adaptive Consensus based Cubature Kalman Filter for Distributed Sensor Networks

Jirong Zha; Liang Han; Zhang Ren

doi:10.1109/CAC53003.2021.9727771

Privacy-Preserving Adaptive Consensus based Cubature Kalman Filter for Distributed Sensor Networks

Jirong Zha
, Liang Han^*
, Zhang Ren

^*Corresponding author for this work

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Information security is an unsolved problem of existing distributed state estimation. In this paper, a privacy-preserving adaptive consensus-based cubature Kalman filter (PAC-CKF) with certain estimation accuracy and convergence speed is proposed to improve the information security of distributed sensor networks. By combining the state-decomposition mechanism with adaptive average consensus in the frame of cubature Kalman filter, the proposed algorithm can ensure both the network security and estimation accuracy under limited consensus iterations. Simulations are performed to demonstrate the effectiveness of estimation accuracy, privacy preservation, and convergence rate of the proposed algorithm.

Original language	English
Title of host publication	Proceeding - 2021 China Automation Congress, CAC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6874-6879
Number of pages	6
ISBN (Electronic)	9781665426473
DOIs	https://doi.org/10.1109/CAC53003.2021.9727771
State	Published - 2021
Event	2021 China Automation Congress, CAC 2021 - Beijing, China Duration: 22 Oct 2021 → 24 Oct 2021

Publication series

Name	Proceeding - 2021 China Automation Congress, CAC 2021

Conference

Conference	2021 China Automation Congress, CAC 2021
Country/Territory	China
City	Beijing
Period	22/10/21 → 24/10/21

Keywords

adaptive average consensus
cubature Kalman filter
distributed estimation
Privacy preservation
sensor network

Access to Document

10.1109/CAC53003.2021.9727771

Cite this

@inproceedings{7b340e851ced46f4afdcafa210574b42,

title = "Privacy-Preserving Adaptive Consensus based Cubature Kalman Filter for Distributed Sensor Networks",

abstract = "Information security is an unsolved problem of existing distributed state estimation. In this paper, a privacy-preserving adaptive consensus-based cubature Kalman filter (PAC-CKF) with certain estimation accuracy and convergence speed is proposed to improve the information security of distributed sensor networks. By combining the state-decomposition mechanism with adaptive average consensus in the frame of cubature Kalman filter, the proposed algorithm can ensure both the network security and estimation accuracy under limited consensus iterations. Simulations are performed to demonstrate the effectiveness of estimation accuracy, privacy preservation, and convergence rate of the proposed algorithm.",

keywords = "adaptive average consensus, cubature Kalman filter, distributed estimation, Privacy preservation, sensor network",

author = "Jirong Zha and Liang Han and Zhang Ren",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 China Automation Congress, CAC 2021 ; Conference date: 22-10-2021 Through 24-10-2021",

year = "2021",

doi = "10.1109/CAC53003.2021.9727771",

language = "英语",

series = "Proceeding - 2021 China Automation Congress, CAC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "6874--6879",

booktitle = "Proceeding - 2021 China Automation Congress, CAC 2021",

address = "美国",

}

Zha, J, Han, L & Ren, Z 2021, Privacy-Preserving Adaptive Consensus based Cubature Kalman Filter for Distributed Sensor Networks. in Proceeding - 2021 China Automation Congress, CAC 2021. Proceeding - 2021 China Automation Congress, CAC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 6874-6879, 2021 China Automation Congress, CAC 2021, Beijing, China, 22/10/21. https://doi.org/10.1109/CAC53003.2021.9727771

Privacy-Preserving Adaptive Consensus based Cubature Kalman Filter for Distributed Sensor Networks. / Zha, Jirong; Han, Liang ; Ren, Zhang.
Proceeding - 2021 China Automation Congress, CAC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 6874-6879 (Proceeding - 2021 China Automation Congress, CAC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Privacy-Preserving Adaptive Consensus based Cubature Kalman Filter for Distributed Sensor Networks

AU - Zha, Jirong

AU - Han, Liang

AU - Ren, Zhang

PY - 2021

Y1 - 2021

N2 - Information security is an unsolved problem of existing distributed state estimation. In this paper, a privacy-preserving adaptive consensus-based cubature Kalman filter (PAC-CKF) with certain estimation accuracy and convergence speed is proposed to improve the information security of distributed sensor networks. By combining the state-decomposition mechanism with adaptive average consensus in the frame of cubature Kalman filter, the proposed algorithm can ensure both the network security and estimation accuracy under limited consensus iterations. Simulations are performed to demonstrate the effectiveness of estimation accuracy, privacy preservation, and convergence rate of the proposed algorithm.

AB - Information security is an unsolved problem of existing distributed state estimation. In this paper, a privacy-preserving adaptive consensus-based cubature Kalman filter (PAC-CKF) with certain estimation accuracy and convergence speed is proposed to improve the information security of distributed sensor networks. By combining the state-decomposition mechanism with adaptive average consensus in the frame of cubature Kalman filter, the proposed algorithm can ensure both the network security and estimation accuracy under limited consensus iterations. Simulations are performed to demonstrate the effectiveness of estimation accuracy, privacy preservation, and convergence rate of the proposed algorithm.

KW - adaptive average consensus

KW - cubature Kalman filter

KW - distributed estimation

KW - Privacy preservation

KW - sensor network

UR - https://www.scopus.com/pages/publications/85128085358

U2 - 10.1109/CAC53003.2021.9727771

DO - 10.1109/CAC53003.2021.9727771

M3 - 会议稿件

AN - SCOPUS:85128085358

T3 - Proceeding - 2021 China Automation Congress, CAC 2021

SP - 6874

EP - 6879

BT - Proceeding - 2021 China Automation Congress, CAC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 China Automation Congress, CAC 2021

Y2 - 22 October 2021 through 24 October 2021

ER -

Privacy-Preserving Adaptive Consensus based Cubature Kalman Filter for Distributed Sensor Networks

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this