The Cramér–Rao Bounds and Sensor Selection for Nonlinear Systems with Uncertain Observations
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[1] Petr Tichavský,et al. Filtering, predictive, and smoothing Cramér-Rao bounds for discrete-time nonlinear dynamic systems , 2001, Autom..
[2] Bruno Sinopoli,et al. Kalman filtering with intermittent observations , 2004, IEEE Transactions on Automatic Control.
[3] Jeff A. Bilmes,et al. A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models , 1998 .
[4] Y. Bar-Shalom,et al. The Cramer-Rao bound for dynamic target tracking with measurement origin uncertainty , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..
[5] Xiaojun Yang,et al. Sparsity-promoting sensor selection for nonlinear target tracking with quantized data , 2017, 2017 20th International Conference on Information Fusion (Fusion).
[6] Pramod K. Varshney,et al. Conditional Posterior Cramér-Rao Lower Bounds for Nonlinear Sequential Bayesian Estimation , 2011, IEEE Trans. Signal Process..
[7] James H. Taylor. The Cramer-Rao estimation error lower bound computation for deterministic nonlinear systems , 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.
[8] Mohamed T. Hadidi,et al. Linear recursive state estimators under uncertain observations , 1978 .
[9] Donghua Wang,et al. Globally Optimal Multisensor Distributed Random Parameter Matrices Kalman Filtering Fusion with Applications , 2008, Sensors.
[10] Kristine L. Bell,et al. A Lower Bound on the Estimation Error for Markov Processes , 2007 .
[11] C. Chang. Two lower bounds on the covariance for nonlinear estimation problems , 1981 .
[12] Pramod K. Varshney,et al. Sensor Selection Based on Generalized Information Gain for Target Tracking in Large Sensor Networks , 2013, IEEE Transactions on Signal Processing.
[13] Branko Ristic,et al. A comparison of two Crame/spl acute/r-Rao bounds for nonlinear filtering with P/sub d/<1 , 2004, IEEE Transactions on Signal Processing.
[14] Ping Wang,et al. The estimation fusion and Cramer-Rao bounds for nonlinear systems with uncertain observations , 2017, 2017 20th International Conference on Information Fusion (Fusion).
[15] Rekha Jain,et al. Wireless Sensor Network -A Survey , 2013 .
[16] Pramod K. Varshney,et al. Sensor selection for nonlinear systems in large sensor networks , 2014, IEEE Transactions on Aerospace and Electronic Systems.
[17] Gerhard P. Hancke,et al. Industrial Wireless Sensor Networks: Challenges, Design Principles, and Technical Approaches , 2009, IEEE Transactions on Industrial Electronics.
[18] Nasser E. Nahi,et al. Optimal recursive estimation with uncertain observation , 1969, IEEE Trans. Inf. Theory.
[19] Harry L. Van Trees,et al. Detection, Estimation, and Modulation Theory, Part I , 1968 .
[20] Yaakov Oshman,et al. A Crame/spl acute/r-Rao-type estimation lower bound for systems with measurement faults , 2005, IEEE Transactions on Automatic Control.
[21] Hui Zhang,et al. Robust weighted H∞ filtering for networked systems with intermittent measurements of multiple sensors , 2011 .
[22] Shu-Li Sun,et al. State Estimation for a Class of Non-Uniform Sampling Systems with Missing Measurements , 2016, Sensors.
[23] Oswaldo Luiz V. Costa,et al. Stationary filter for linear minimum mean square error estimator of discrete-time Markovian jump systems , 2002, IEEE Trans. Autom. Control..
[24] Sundeep Prabhakar Chepuri,et al. Sparsity-Promoting Sensor Selection for Non-Linear Measurement Models , 2013, IEEE Transactions on Signal Processing.
[25] Myo-Taeg Lim,et al. Improving Reliability of Particle Filter-Based Localization in Wireless Sensor Networks via Hybrid Particle/FIR Filtering , 2015, IEEE Transactions on Industrial Informatics.
[26] Carlos H. Muravchik,et al. Posterior Cramer-Rao bounds for discrete-time nonlinear filtering , 1998, IEEE Trans. Signal Process..
[27] Nianxia Cao,et al. Sensor Selection for Target Tracking in Wireless Sensor Networks With Uncertainty , 2015, IEEE Transactions on Signal Processing.
[28] Stephen P. Boyd,et al. Sensor Selection via Convex Optimization , 2009, IEEE Transactions on Signal Processing.
[29] Edwin Engin Yaz,et al. Robust minimum variance linear state estimators for multiple sensors with different failure rates , 2007, Autom..
[30] Pramod K. Varshney,et al. Optimal Periodic Sensor Scheduling in Networks of Dynamical Systems , 2013, IEEE Transactions on Signal Processing.
[31] Y. Bar-Shalom,et al. Low observable target motion analysis using amplitude information , 1995, Proceedings of 1995 American Control Conference - ACC'95.
[32] N. Gordon,et al. Cramer-Rao bounds for non-linear filtering with measurement origin uncertainty , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).
[33] J. Galdos. A cramér-rao bound for multidimensional discrete-time dynamical systems , 1980 .
[34] M. Zakai,et al. A lower bound on the estimation error for Markov processes , 1975 .
[35] Branko Ristic,et al. Cramer-Rao bound for nonlinear filtering with Pd<1 and its application to target tracking , 2002, IEEE Trans. Signal Process..