Abstract
This paper addresses the optimal deconvolution estimation problem for measurement-delay systems over a network subject to random packet dropout, which is modeled by independent and identically distributed Bernoulli processes. First, the state estimator problem is solved by utilizing the reorganized innovation analysis approach, which is given in the linear minimum mean square error sense (LMMSE). Then, the noise estimator is obtained based on the state estimator and the projection formula. Last, we provide a numerical example to declare that our proposed estimation approach is effective.
Keywords
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Sadreazami H, Ahmad MO, Swamy MNS (2015) A robust multiplicative watermark detector for color images in sparse domain. IEEE Trans Circuits Syst II: Express Briefs 62(12):1159–1163
Mendel JM (1977) White-noise estimators for seismic date processing in oil exploration. IEEE Trans Autom Control 22(5):694–706
Mendel JM (1981) Minimun variance deconvolution. IEEE Trans Geosci Remote Sens 19(3):161–171
Deng Z, Zhang H, Liu S, Zhou L (1996) Optimal and self-tuning white noise estimators with application to deconvolution and filtering problem. Automatica 32(2):199–216
Xiao L, Hassibi A, How JP (2000) Control with random communication delays via a discrete-time jump system approach. In: Proceedings of the American Control Conference, pp 2199–2204
Wu X, Song X, Yan X (2015) Optimal estimation problem for discrete-time systems with multi-channel multiplicative noise. Int J Innov Comput Inf Control 11(6):1881–1895
Song IY, Kim DY, Shin V, Jeon M (2012) Receding horizon filtering for discrete-time linear systems with state and observation delays. IET Radar Sonar Navig 6(4):263–271
Nahi NE (1969) Optimal recursive estimation with uncertain observation. IEEE Trans Inf Theory 15(4):457–462
Sinopoli B, Schenato L, Franceschetti M, Poolla K, Jordan M, Sastry S (2004) Kalman filtering with intermittent observations. IEEE Trans Autom Control 49(9):1453–1464
Liu X, Goldmith A (2004) Kalman filtering with partial observation losses. In: Proceeding of the 43rd IEEE Conference on Decision and Control, pp 4180–4186
Gao S, Chen P (2014) Suboptimal filtering of networked discrete-time systems with random observation losses. In: Mathematical Problems in Engineering
Zhang H, Song X, Shi L (2012) Convergence and mean square stability of suboptimal estimator for systems with measurement packet dropping. IEEE Trans Autom Control 57(5):1248–1253
Han C, Wang W (2013) Deconvolution estimation of systems with packet dropouts. In: Proceeding of the 25th Chinese Control and Decision Conference, pp 4588–4593
Sun S (2013) Optimal linear filters for discrete-time systems with randomly delayed and lost measurements with/without time stamps. IEEE Trans Autom Control 58(6):1551–1556
Wang S, Fang H, Tian X (2015) Recusive estimation for nonlinear stochastic systems with multi-step transmission delay, multiple packet droppouts and correlated noises. Signal Process 115:164–175
Feng J, Wang T, Guo J (2014) Recursive estimation for descriptor systems with multiple packet dropouts and correlated noises. Aerosp Sci Technol 32(1):200–211
Li F, Zhou J, Wu D (2013) Optimal filtering for systems with finite-step autocorrelated noises and multiple packet dropouts. Aerosp Sci Technol 24(1):255–263
Horn RA, Johnson CR (1991) Topic in Matrix Analysis. Cambridge University Press, New York
Zhang H, Xie L, Zhang D, Soh YC (2004) A reorganized innovation approach to linear estimation. IEEE Trans Autom Control 49(10):1810–1814
Acknowledgments
This work is supported in part by the Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology, the Excellent Young Scholars Research Fund of Shandong Normal University, and the National Natural Science Foundation of China (61304013).
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© 2016 Springer Science+Business Media Singapore
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Duan, Z., Song, X., Yan, X. (2016). Deconvolution Estimation Problem for Measurement-Delay Systems with Packet Dropping. In: Jia, Y., Du, J., Zhang, W., Li, H. (eds) Proceedings of 2016 Chinese Intelligent Systems Conference. CISC 2016. Lecture Notes in Electrical Engineering, vol 404. Springer, Singapore. https://doi.org/10.1007/978-981-10-2338-5_32
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DOI: https://doi.org/10.1007/978-981-10-2338-5_32
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