Abstract
In centralized multisensor tracking systems, there are out-of-sequence measurements (OOSMs) frequently arising due to different time delays in communication links and varying pre-processing times at the sensor. Such OOSM arrival can induce the “negative-time measurement update” problem, which is quite common in real multisensor tracking systems. The A1 optimal update algorithm with OOSM is presented by Bar-Shalom for one-step case. However, this paper proves that the optimality of A1 algorithm is lost in direct discrete-time model (DDM) of the process noise, it holds true only in discretized continuous-time model (DCM). One better OOSM filtering algorithm for DDM case is presented. Also, another new optimal OOSM filtering algorithm, which is independent of the discrete time model of the process noise, is presented here. The performance of the two new algorithms is compared with that of A1 algorithm by Monte Carlo simulations. The effectiveness and correctness of the two proposed algorithms are validated by analysis and simulation results.
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References
Bar-Shalom Y, Li X R. Multitarget-multisensor Tracking: Principles and Techniques. Storrs, CT: YBS Publishing, 1995
Blackman S S, Popoli R. Design and Analysis of Modern Tracking Systems. Boston: Artech House, 1999
Mallick M, Coraluppi S, Carthel C. Advances in asynchronous and decentralized estimation. In: IEEE Proc. Aerospace Conference, Big Sky, MT, Mar. 2001. 1873–1888
Thomopoulos S C A, Zhang L. Distributed filtering with random sampling and delay. In: Proceedings of the 27th IEEE Conference on Decision and Control. Vol. 3, Austin, Texas, 1988. 2348–2353
Hilton R D, Martin D A, Blair W D. Tracking with time-delayed data in multisensor systems. Technical Report NSWCDD/TR-93/351, AD-A355269, Dahlgren, VA, August 1993
Bar-Shalom Y. Update with out-of-sequence measurements in tracking: Exact solution. In: Oliver E, Drummond, ed. Signal and Data Processing of Small Targets 2000. Proceedings of SPIE, Vol. 4080, 2000. 541–556
Wang H, Kirubarajan T, Bar-Shalom Y. Precision large scale air traffic surveillance using IMM/assignment estimators. IEEE Trans Aerospace Electron Syst, 1999, 35(1): 255–266
Bar-Shalom Y. Update with out-of-sequence measurements in tracking: Exact solution. IEEE Trans Aerospace Electron Syst, 2002, 38(3): 769–777
Bar-Shalom Y, Chen H M, Mallick M. One-step solution for the multistep out-of-sequence-measurement problem in tracking. IEEE Trans Aerospace Electron Syst, 2004, 40(1): 27–37
Bar-Shalom Y, Chen H M. IMM estimator with out-of-sequence measurements. IEEE Trans Aerospace Electron Syst, 2005, 41(1): 90–98
Bar-Shalom Y, Li X R, Kirubarajan T. Estimation with Application to Tracking and Navigation. New York: John Wiley & Sons, 2001
Li X R, Jilkov V P. Survey of maneuvering target tracking. Part I: Dynamic models. IEEE Trans Aerospace Electron Syst, 2003, 39(4): 1333–1364
Li X R. Recursibility and optimal recursive linear estimation and filtering. In: Proceedings of the 43rd IEEE Conference on Decision and Control, Paradise Island, Bahamas, Dec. 2004. 1761–1766
Rhodes I B. A tutorial introduction to estimation and filtering. IEEE Trans Autom Control, 1971, 16(6): 688–704
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Supported by the National Natural Science Foundation of China (Grant No. 60402033)
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Zhou, W., Li, L., Chen, G. et al. Optimality analysis of one-step OOSM filtering algorithms in target tracking. SCI CHINA SER F 50, 170–187 (2007). https://doi.org/10.1007/s11432-007-0012-y
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DOI: https://doi.org/10.1007/s11432-007-0012-y