Identification and distributed fusion filter for multi-sensor networked systems with stochastic deception attacks
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Guangyao He, Shuli SunAuthors Info & Claims
References
[1]
J. Hu, Z. Wang, D. Chen, F. Alsaadi, Estimation, filtering and fusion for networked systems with network-induced phenomena: new progress and prospects, Information Fusion 31 (2016) 65–75.
[2]
S. Sun, H. Lin, J. Ma, X. Li, Multi-sensor distributed fusion estimation with applications in networked systems: a review paper, Information Fusion 38 (2017) 122–134.
[3]
N. Carlson, Federated square root filter for decentralized parallel processes, IEEE Trans. Aerosp. Electron. Syst. 26 (3) (1990) 517–525.
[4]
X. Li, Y. Zhu, J. Wang, C. Han, Optimal linear estimation fusion—Part I: unified fusion rules, IEEE Trans. Inf. Theory 49 (9) (2003) 2192–2208.
[5]
S. Sun, Z. Deng, Multi-sensor optimal information fusion Kalman filter, Automatica 40 (6) (2004) 1017–1023.
[6]
S. Julier, J. Uhlmann, A non-divergent estimation algorithm in the presence of unknown correlation, in: American Control Conference, Albuquerque, NM, 1997, pp. 2369–2373.
[7]
T. Tian, S. Sun, N. Li, Multi-sensor information fusion estimators for stochastic uncertain systems with correlated noises, Information Fusion 27 (2016) 126–137.
[8]
R. Caballero, A. Hermoso, J. Linares, Distributed fusion filters from uncertain measured outputs in sensor networks with random packet losses, Information Fusion 34 (2017) 70–79.
[9]
Y. Wei, S. Sun, Recursive distributed fusion estimation for multi-sensor systems with missing measurements, multiple random transmission delays and packet losses, Signal Processing 204 (2023).
[10]
D. Ding, Z. Wang, D.W.C. Ho, G. Wei, Distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor network, Automatica 78 (2017) 231–240.
[11]
B. Shen, Z. Wang, D. Wang, et al., State-saturated recursive filter design for stochastic time-varying nonlinear complex networks under deception attacks, IEEE Trans. Neural. Netw. Learn. Syst. 31 (10) (2020) 3788–3800.
[12]
R. Caballero-Águila, J. Hu, J. Linares-Pérez, Two compensation strategies for optimal estimation in sensor networks with random matrices, time-correlated noises, deception attacks and packet losses, Sensors 22 (21) (2022) 8505.
[13]
W. Qian, D. Lu, S.M. Guo, Y.J. Zhao, Distributed state estimation for mixed delays system over sensor networks with multichannel random attacks and Markov switching topology, IEEE Trans. Neural. Netw. Learn. Syst., 2024,. in pressDOI.
[14]
L. Ma, Z. Wang, Q.L. Han, H.K. Lam, Variance-constrained distributed filtering for time-varying systems with multiplicative noises and deception attacks over sensor networks, IEEE Sens. J. 17 (7) (2017) 2279–2288.
[15]
M. Li, Y. Chen, Y. Zhang, Y. Liu, Adaptive sliding-mode tracking control of networked control systems with false data injection attacks, Inf. Sci. (Ny) 585 (2022) 194–208.
[16]
G. Cao, W. Gu, G. Lou, et al., Distributed synchronous detection for false data injection attack in cyber-physical microgrids, Int. J. Electric. Power Energy Syst. 137 (2022) 1–8.
[17]
B. Chen, D.W.C. Ho, W.A. Zhang, L. Yu, Distributed dimensionality reduction fusion estimation for cyber-physical systems under DoS attacks, IEEE Trans. Syst., Man, Cybernetics: Systems 49 (2) (2019) 455–468.
[18]
J. Liu, E. Gong, L. Zha, et al., Interval type-2 fuzzy-model-based filtering for nonlinear systems with event-triggering weighted try-once-discard protocol and cyberattacks, IEEE Trans. Fuzzy Syst. 32 (3) (2024) 721–732.
[19]
L. Zha, Y. Guo, J. Liu, et al., Protocol-based distributed security fusion estimation for time-varying uncertain systems over sensor networks: tackling DoS attacks, IEEE Trans Signal Inf Process Netw 10 (2024) 119–130.
[20]
L. Zhang, S. Sun, Distributed H∞ fusion filtering for multi-sensor networked systems with DoS attacks and sensor saturations, Digit Signal Process 134 (2023).
[21]
T. Wan, S. Sun, Fusion identification and estimation of multisensor multichannel AR signals with missing measurements and sensor biases, Digit Signal Process 98 (2020) 1–11.
[22]
G. Duan, S. Sun, Self-tuning distributed fusion filter for multi-sensor systems subject to unknown model parameters and missing measurement rates, IEEE Access 6 (2018) 61519–61528.
[23]
M. Wang, S. Sun, Self-tuning distributed fusion filter for multi-sensor networked systems with unknown packet receiving rates, noise variances, and model parameters, Sensors 19 (20) (2019) 1–17.
[24]
Y. Ma, S. Sun, Distributed optimal and self-tuning filters based on compressed data for networked stochastic uncertain systems with deception attacks, Sensors 23 (1) (2023) 335.
[25]
L. Li, H. Yang, Y. Xia, L. Dai, Distributed filtering for nonlinear systems under false data injection attack, Automatica 145 (2022) 1–9.
[26]
Z. Deng, Information Fusion Estimation Theory and Applications, Science Press, Beijing, 2012.
[27]
S. Hu, Automatic Control Theory, Science Press, Beijing, 2006.
[28]
J. Liu, G. Hao, Fast covariance intersection fusion weighted by diagonal matrix cubature Kalman filter, Control Theory Appl. 40 (2) (2023) 313–321.
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Elsevier Inc.
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Academic Press, Inc.
United States
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Published: 18 July 2024
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