Optimal distributed Kalman filtering fusion for a linear dynamic system with cross-correlated noises

References

• Anderson , BDO and Moore , JB . 1979 . Optimal Filtering , Englewood Cliffs, NJ : Prentice-Hall .
   Google Scholar
• Bar-Shalom , Y . 1990 . Multitarget-multisensor Tracking: Advanced Applications , Vol. 1 , Norwood, MA : Atech House .
   Google Scholar
• Basin , MV , Alcorta-Garcia , MA and Alanis-Duran , A . 2008 . Optimal Filtering for Linear Systems with State and Multiple Observation Delays . International Journal of Systems Science , 39 : 547 – 555 .
   Web of Science ®Google Scholar
• Basin , MV , Sanchez , EN and Martnez-Zuniga , R . 2007 . Optimal Linear Filtering for Systems with Multiple State and Observation Delays . International Journal of Innovative Computing, Information and Control , 3 : 1309 – 1320 .
   Web of Science ®Google Scholar
• Basin , MV , Shi , P and Alanis-Duran , A . 2010 . Central Suboptimal H ∞ Filter Design for Linear Time-varying Systems with State and Measurement Delays . International Journal of Systems Science , 41 : 411 – 421 .
   Web of Science ®Google Scholar
• Chen , H , Kirubarajan , T and Bar-Shalom , Y . 2003 . Performance Limits of Track-to-track Fusion Versus Centralized Estimation: Theory and Application . IEEE Transactions on Aerospace and Electronic Systems , 39 : 386 – 400 .
   Web of Science ®Google Scholar
• Chong , CY , Chang , KC and Mori , S . 1986 . Distributed Tracking in Distributed Sensor Networks . Proceedings of the 1986 American Control Conference . 1986 . Seattle, WA
   Google Scholar
• Chong , CY , Mori , S and Chang , KC . 1990 . “ Distributed Multitarget Multisensor Tracking ” . In Multitarget-Multisensor Tracking: Advanced Applications , Edited by: Bar-Shalom , Y . Vol. 1 , 247 – 295 . Norwood, MA : Atech House .
   Google Scholar
• Dong , H , Wang , Z and Gao , H . 2010 . Robust H ∞ Filtering for a Class of Nonlinear Networked Systems with Multiple Stochastic Communication Delays and Packet Dropouts . IEEE Transactions on Signal Processing , 58 : 1957 – 1966 .
   Web of Science ®Google Scholar
• Dong , H , Wang , Z , Ho , DWC and Gao , H . 2010 . Variance-constrained H ∞ Filtering for Nonlinear Time-varying Stochastic Systems with Multiple Missing Measurements: the Finite-horizon Case . IEEE Transactions on Signal Processing , 58 : 2534 – 2543 .
   Web of Science ®Google Scholar
• Fitzgerald , RJ . 2000 . Analytic Track Solutions with Range-dependent Errors . IEEE Transactions on Aerospace and Electronic Systems , 36 : 343 – 348 .
   Web of Science ®Google Scholar
• Gan , Q and Harris , CJ . 2001 . Comparison of Two Measurement Fusion Methods for Kalman-filter-based Multisensor Data Fusion . IEEE Transactions on Aerospace and Electronic Systems , 37 : 273 – 280 .
   Web of Science ®Google Scholar
• Gao , H , Meng , X and Chen , T . 2008 . A New Design of Robust H 2 Filters for Uncertain Systems . Systems and Control Letters , 57 : 585 – 593 .
   Web of Science ®Google Scholar
• Gao , H , Meng , X and Chen , T . 2009 . H ∞ Filter Design for Discrete Delay Systems: A New Parameter-dependent Approach . International Journal of Control , 82 : 993 – 1005 .
   Web of Science ®Google Scholar
• Hashemipour , HR , Roy , S and Laub , AJ . 1988 . Decentralized Structures for Parallel Kalman Filtering . IEEE Transactions on Automatic Control , 33 : 88 – 93 .
   Web of Science ®Google Scholar
• He , Y , Lu , D and Peng , Y . 1999 . State Estimation for Multilevel Multisensor Data Fusion Systems . Acta Electronica Sinica , 27 : 60 – 63 .
   Google Scholar
• Li , X and Jilkov , VP . 2003 . Survey of Maneuvering Target Tracking: Part I. Dynamic Models . IEEE Transactions on Aerospace and Electronic Systems , 39 : 1333 – 1364 .
   Web of Science ®Google Scholar
• Li , X , Zhu , Y , Wang , J and Han , C . 2003 . Optimal Linear Estimation Fusion: I. Unified Fusion Rules . IEEE Transactions on Information Theory , 49 : 2192 – 2208 .
   Web of Science ®Google Scholar
• Liang , J and Lam , J . 2010 . Robust State Estimation for Stochastic Genetic Regulatory Networks . International Journal of Systems Science , 41 : 47 – 63 .
   Web of Science ®Google Scholar
• Roy , S and Iitis , RA . 1991 . Decentralized Linear Estimation in Correlated Measurement Noise . IEEE Transactions on Aerospace and Electronic Systems , 27 : 939 – 941 .
   Web of Science ®Google Scholar
• Shen , B , Wang , Z , Shu , H and Wei , G . 2009 . H ∞ Filtering for Nonlinear Discrete-time Stochastic Systems with Randomly Varying Sensor Delays . Automatica , 45 : 1032 – 1037 .
   Web of Science ®Google Scholar
• Song , E , Zhu , Y , Zhou , J and You , Z . 2007 . Optimal Kalman Filtering Fusion with Cross-correlated Sensor Noises . Automatica , 43 : 1450 – 1456 .
   Web of Science ®Google Scholar
• Sun , S and Deng , Z . 2004 . Multi-sensor Optimal Information Fusion Kalman Filter . Automatica , 40 : 1017 – 1023 .
   Web of Science ®Google Scholar
• Wang , Z , Lam , J , Wei , G , Fraser , K and Liu , X . 2008 . Filtering for Nonlinear Genetic Regulatory Networks with Stochastic Disturbances . IEEE Transactions on Automatic Control , 53 : 2448 – 2457 .
   Web of Science ®Google Scholar
• Wang , Z , Liu , Y and Liu , X . 2008 . H ∞ Filtering for Uncertain Stochastic Time-delay Systems with Sector-bounded Nonlinearities . Automatica , 44 : 1268 – 1277 .
   Web of Science ®Google Scholar
• Wang , Z , Liu , Y and Liu , X . 2009 . State Estimation for Jumping Recurrent Neural Networks with Discrete and Distributed Delays . Neural Networks , 22 : 41 – 48 .
   PubMed Web of Science ®Google Scholar
• Wang , Z , Liu , X , Liu , X , Liang , J and Vinciotti , V . 2009 . An Extended Kalman Filtering Approach to Modelling Nonlinear Dynamic Gene Regulatory Networks via Short Gene Expression Time Series . IEEE/ACM Transactions on Computational Biology and Bioinformatics , 6 : 410 – 419 .
   PubMed Web of Science ®Google Scholar
• Wen , C , Wen , C and Li , Y . 2008 . “ An Optimal Sequential Decentralized Filter of Discrete-time Systems with Cross-correlated Noises ” . In in Proceedings of the 17th World Congress The International Federation of Automatic Control 7560 – 7565 . Seoul, Korea
   Google Scholar
• Willner , D , Chang , CB and Dunn , KP . 1976 . Kalman Filter Algorithm for a Multisensor System . Proceedings of the 15th IEEE Conference on Decision and Control (Vol. 15) . 1976 . Vol. 15 , pp. 570 – 574 .
   Google Scholar
• Yu , W , Chen , G , Wang , Z and Yang , W . 2009 . Distributed Consensus Filtering in Sensor Networks . IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics , 39 : 1568 – 1577 .
   PubMed Web of Science ®Google Scholar
• Zhang , H , Basin , MV and Skliar , M . 2007 . Ito-Volterra Optimal State Estimation with Continuous, Multirate, Randomly Sampled, and Delayed Measurements . IEEE Transactions on Automatic Control , 52 : 401 – 416 .
   Web of Science ®Google Scholar
• Zhou , Z , Hu , C , Chen , M , He , H and Zhang , B . 2010 . An Improved Fuzzy Kalman Filter for State Estimation of Non-linear Systems . International Journal of Systems Science , 41 : 537 – 546 .
   Web of Science ®Google Scholar
• Zhu , Y , You , Z , Zhao , J , Zhang , K and Li , X . 2001 . The Optimality for Distributed Kalman Filtering Fusion with Feedback . Automatica , 37 : 1489 – 1493 .
   Web of Science ®Google Scholar