Robust fusion steady‐state estimators for networked stochastic uncertain systems with packet dropouts and missing measurements

[1]  Xin Wang,et al.  Optimal recursive estimation for networked stochastic uncertain systems with fading measurements and time-correlated channel noises , 2019, J. Comput. Appl. Math..

[2]  Jing Ma,et al.  Multi-sensor distributed fusion estimation with applications in networked systems: A review paper , 2017, Inf. Fusion.

[3]  Shu-Li Sun,et al.  Multi-sensor optimal information fusion Kalman filter , 2004, Autom..

[4]  Long Xu,et al.  Optimal filtering for systems with finite-step autocorrelated process noises, random one-step sensor delay and missing measurements , 2016, Commun. Nonlinear Sci. Numer. Simul..

[5]  Yunmin Zhu,et al.  The optimality for the distributed Kalman filtering fusion with feedback , 2001, Autom..

[6]  Mahmood R. Azimi-Sadjadi,et al.  Two-dimensional adaptive block Kalman filtering of SAR imagery , 1991, IEEE Trans. Geosci. Remote. Sens..

[7]  Chunshan Yang,et al.  Robust weighted state fusion Kalman estimators for networked systems with mixed uncertainties , 2018, Inf. Fusion.

[8]  Peng Zhang,et al.  Robust weighted fusion Kalman filters for multisensor time-varying systems with uncertain noise variances , 2014, Signal Process..

[9]  Deng Zili,et al.  Robust time‐varying Kalman estimators for systems with packet dropouts and uncertain‐variance multiplicative and linearly correlated additive white noises , 2018 .

[10]  Jing Ma,et al.  Distributed fusion filter for networked stochastic uncertain systems with transmission delays and packet dropouts , 2017, Signal Process..

[11]  Yuan Gao,et al.  New approach to information fusion steady-state Kalman filtering , 2005, Autom..

[12]  Wenqiang Liu,et al.  Robust weighted fusion Kalman estimators for multisensor systems with multiplicative noises and uncertain‐covariances linearly correlated white noises , 2017 .

[13]  Wen‐Qiang Liu,et al.  Robust fusion steady‐state filtering for multisensor networked systems with one‐step random delay, missing measurements, and uncertain‐variance multiplicative and additive white noises , 2019 .

[14]  Nasser E. Nahi,et al.  Optimal recursive estimation with uncertain observation , 1969, IEEE Trans. Inf. Theory.

[15]  Zili Deng,et al.  Robust fusion time‐varying Kalman estimators for multisensor networked systems with mixed uncertainties , 2018, International Journal of Robust and Nonlinear Control.

[16]  Fan Wang,et al.  Robust Kalman filters for linear time-varying systems with stochastic parametric uncertainties , 2002, IEEE Trans. Signal Process..

[17]  Daniel W. C. Ho,et al.  Robust filtering under randomly varying sensor delay with variance constraints , 2003, IEEE Transactions on Circuits and Systems II: Express Briefs.

[18]  Xuemei Wang,et al.  Robust centralized and weighted measurement fusion Kalman estimators for uncertain multisensor systems with linearly correlated white noises , 2017, Inf. Fusion.

[19]  Huajing Fang,et al.  Minimum variance estimation for linear uncertain systems with one-step correlated noises and incomplete measurements , 2016, Digit. Signal Process..

[20]  Jing Ma,et al.  Multi-sensor distributed fusion filtering for networked systems with different delay and loss rates , 2014, Digit. Signal Process..

[21]  Fuad E. Alsaadi,et al.  Iterative parameter identification for pseudo-linear systems with ARMA noise using the filtering technique , 2018 .

[22]  Guoqiang Hu,et al.  Networked fusion kalman filtering with multiple uncertainties , 2015, IEEE Transactions on Aerospace and Electronic Systems.

[23]  Lihua Xie,et al.  Optimal linear estimation for systems with multiple packet dropouts , 2008, Autom..

[24]  Chuang Li,et al.  Multi-model information fusion Kalman filtering and white noise deconvolution , 2010, Inf. Fusion.

[25]  Jing Ma,et al.  Optimal Linear Estimators for Systems With Random Sensor Delays, Multiple Packet Dropouts and Uncertain Observations , 2011, IEEE Transactions on Signal Processing.

[26]  Shuli Sun,et al.  Centralized Fusion Estimators for Multisensor Systems With Random Sensor Delays, Multiple Packet Dropouts and Uncertain Observations , 2013, IEEE Sensors Journal.

[27]  Jeffrey K. Uhlmann,et al.  Using covariance intersection for SLAM , 2007, Robotics Auton. Syst..