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TWO FUSION PREDICTORS FOR MULTISENSOR DISCRETETIME LINEAR SYSTEM
H.R. Song, M. Jeon, Y.S. Lee, T.-S. Choi, and V. Shin
References
[1] D.L. Hall, Mathematical techniques in multisensor data fusion(London: Artech House, 1992).
[2] Y.B.-Shalom & X. Rong Li, Multitarget-multisensor tracking:Principles and techniques (Connecticut, USA: YBS Publishing,1995).
[3] Y.B.-Shalom (Ed.), Multitarget-multisensor tracking: Ad-vanced applications (Norwood, MA: Artech House, 1990),194–202.
[4] Y.B.-Shalom & L. Campo, The effect of the common processnoise on the two-sensor fused track covariance, IEEE Trans-actions on Aerospace and Electronic Systems, 22(11), 1986,803–805.
[5] X.R. Li, Y.M. Zhu, J. Wang, & C.Z. Han, Optimal linear esti-mation fusion – Part I: Unified fusion rules, IEEE Transactionson Information Theory, 49(9), 2004, 2192–2208.
[6] V.I. Shin, Y. Lee, & T. Choi, Suboptimal Linear Filtering andGeneralized Millman’s Formula, Proc. IASTED International,Conf. on Signal and Image Process, Honolulu, Hawaii, USA,2004, 369–374.
[7] V. Shin, Y. Lee, & T.S. Choi, Generalized Millman’s formulaand its applications for estimation problems, Signal Processing,86(2), 2006, 257–266.
[8] J. Zhou, Y. Zhu, Z. You, & E. Song, An efficient algorithm foroptimal linear estimation fusion in distributed multisensor sys-tems, IEEE Transactions on Systems, Man, and Cybernetics,36(5), 2006, 1000–1009.
[9] S.L. Sun & Z.L. Deng, Multi-sensor information fusion Kalmanfilter weighted by scalars for systems with colored measure-ment noises, Journal of Dynamic Systems, Measurement andControl, 127(4), 2005, 663–667.
[10] S.L. Sun, Multi-sensor optimal information fusion Kalmanfilters with applications, Aerospace Science and Technology,8(1), 2004, 57–62.
[11] K.C. Chang, R.K. Saha, & Y.B.-shalom, On optimal track totrack fusion with information fusion, IEEE Transactions onAerospace and Electronic Systems, 24(4), 1997, 1271–1275.
[12] K.C. Chang, W. Tian, & R.K. Saha, Performance evaluation oftrack fusion with information matrix filter, IEEE Transactionson Aerospace and Electronic Systems, 38(2), 2002, 455–466.
[13] J.A. Roecker & C.D. McGillem, Comparison of two sensortracking methods based on state vector fusion and measure-ment fusion, IEEE Transactions on Aerospace and ElectronicSystems, 24(4), 1998, 447–449.
[14] Y.M. Zhu, Z. You, J. Zhao, K. Zhang, & X.R. Li, Theoptimality for the distributed Kalman filtering fusion withfeedback, Automatica, 37, 2001, 1489–1493.
[15] Y.B.-Shalom, On hierarchical tracking for the real world, IEEETransactions on Aerospace and Electronic Systems, 42(3),2006, 846–850.
[16] A.T. Alouani & J.E. Gray, Theory of distributed estimationusing multiple asynchronous sensors, IEEE Transactions onAerospace and Electronic Systems, 41(2), 2005, 717–722.
[17] Y.B.-Shalom, X.R. Li, & T. Kirubarajan, Estimation withapplications to tracking and navigation (New York, USA: JohnWiley & Sons, 2001).
[18] F.L. Lewis, Optimal estimation with an introduction to stochas-tic control theory (New York, USA: John Wiley & Sons, 1986).
[19] Y.M. Zhu, Multisensor decision and estimation fusion (Boston,USA: Kluwer, 2002).
[20] Y.M. Zhu & X.R. Li, Best linear unbiased estimation fusion,Proc. International Conf. on Multisource-Multisensor Inf. Fu-sion, Sunnyvale, USA, 1999, 1054–1061.344
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Abstract
DOI:
10.2316/Journal.206.2009.4.206-3233
From Journal
(206) International Journal of Robotics and Automation - 2009
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