Information fusion algorithms for state estimation in multi-sensor systems with correlated missing measurements

Applied Mathematics and Computation

Volumn 226, Issue , 2014, Pages 548-563

  Caballero Aguila R ^a   Garcia Garrido I ^b   Linares Perez J ^b  

^a UNIVERSITY OF JAÉN   (Spain)

^b UNIVERSITY OF GRANADA   (Spain)

Author keywords

Centralized fusion estimation; Distributed fusion estimation; Least squares estimation; Missing observations; Multi sensor systems

Indexed keywords

CENTRALIZED FUSION; DISTRIBUTED FUSION; LEAST-SQUARES ESTIMATION; MISSING OBSERVATIONS; MULTI-SENSOR SYSTEMS;

COVARIANCE MATRIX; SENSORS; SIGNAL FILTERING AND PREDICTION;

ESTIMATION;

EID: 84888627799     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amc.2013.10.068     Document Type: Article

References (26)

1. J. Hespanha, P. Naghshtabrizi, and Yonggang Xu A survey of recent results in networked control systems Proc. IEEE 95 1 2007 138 162
2. L. Ma, Z. Wang, J. Hu, Y. Bo, and Z. Guo Robust variance-constrained filtering for a class of nonlinear stochastic systems with missing measurements Signal Process. 90 2010 2060 2071
3. A. Hermoso-Carazo, and J. Linares-Pérez Nonlinear estimation applying an unscented transformation in systems with correlated uncertain observations Appl. Math. Comput. 217 2011 7998 8009
4. H filtering for discrete-time systems with randomly varying sensor delays Automatica 44 2008 1918 1922
5. S. Nakamori, A. Hermoso-Carazo, and J. Linares-Pérez Design of RLS Wiener estimators from randomly delayed observations in linear discrete-time stochastic systems Appl. Math. Comput. 217 2010 3801 3815
6. S.L. Sun Optimal estimators for systems with finite consecutive packet dropouts IEEE Signal Process. Lett. 16 7 2009 557 560
7. R. Caballero-Águila, A. Hermoso-Carazo, and J. Linares-Pérez Recursive least-squares quadratic smoothing from measurements with packet dropouts Signal Process. 92 2012 931 938
8. S. Sun, and W. Xiao Optimal linear estimators for systems with multiple random measurement delays and packet dropouts Int. J. Syst. Sci. 2011 1 13
9. M. Moayedi, Y.K. Foo, and Y.C. Soh Adaptive Kalman filtering in networked systems with random sensor delays, multiple packet dropouts and missing measurements IEEE Trans. Signal Process. 58 3 2010 1577 1588
10. J. Ma, and S.L. Sun Optimal linear estimators for systems with random sensor delays, multiple packet dropouts and uncertain observations IEEE Trans. Signal Process. 59 11 2011 5181 5192
11. F.O. Hounkpevi, and E.E. Yaz Robust minimum variance linear state estimators for multiple sensors with different failure rates Automatica 43 2007 1274 1280 (Pubitemid 46813124)
12. R. Caballero-Águila, A. Hermoso-Carazo, and J. Linares-Pérez Linear and quadratic estimation using uncertain observations from multiple sensors with correlated uncertainty Signal Process. 91 2011 330 337
13. F.O. Hounkpevi, and E.E. Yaz Minimum variance generalized state estimators for multiple sensors with different delay rates Signal Process. 87 2007 602 613 (Pubitemid 44751165)
14. J. Linares-Pérez, A. Hermoso-Carazo, R. Caballero-Águila, and J.D. Jiménez-López Least-squares linear filtering using observations coming from multiple sensors with one- or two-step random delay Signal Process. 89 2009 2045 2052
15. J. Ma, and S.L. Sun Information fusion estimators for systems with multiple sensors of different packet dropout rates Inf. Fusion 12 2011 213 222
16. R. Caballero-Águila, A. Hermoso-Carazo, and J. Linares-Pérez Least-squares linear estimators using measurements transmitted by different sensors with packet dropouts Digital Signal Process. 22 2012 1118 1125
17. K.H. Kim, Development of track to track fusion algorithms, in: Proc. Am. Control Conf. Maryland, 1994, pp. 1037-1041.
18. S.L. Sun, and Z.L. Deng Multi-sensor optimal information fusion Kalman filter Automatica 40 2004 1017 1023
19. J. Feng, and M. Zeng Descriptor recursive estimation for multiple sensors with different delay rates Int. J. Control 84 3 2011 584 596
20. M.J. García-Ligero, A. Hermoso-Carazo, and J. Linares-Pérez Distributed and centralized fusion estimation from multiple sensors with Markovian delays Appl. Math. Comput. 219 2012 2932 2948
21. W.-A. Zhang, G. Feng, and L. Yu Multi-rate distributed fusion estimation for sensor networks with packet losses Automatica 48 2012 2016 2028
22. S. Sun, and W. Xiao Distributed weighted fusion estimators with random delays and packet dropping Circuits Syst. Signal Process. 26 4 2007 591 605 (Pubitemid 350123784)
23. J. Sun, and C. Zhang Distributed optimal fusion estimators for multi-sensor systems with bounded random measurement delays and packet dropouts J. Comput. Inf. Syst. 8 10 2012 4087 4094
24. H-consensus filtering in sensor networks with multiple missing measurements: the finite-horizon case Automatica 46 2010 1682 1688
25. B. Chen, L. Yu, W.-A. Zhang, A. Liu, Distributed robust fusion Kalman filtering for uncertain stochastic systems with random delays and missing measurements, in: Proc. 2011 8th Asian Control Conf., 2011, pp. 1288-1293.
26. H fusion filters for a class of discrete-time intelligent systems with time delays and missing measurement Neurocomputing 74 2011 3741 3752