HU Yanyan and ZHOU Donghua, “Time-varying Bias Estimation for Asynchronous Multi-sensor Multi-target Tracking Systems Using STF,” Chinese Journal of Electronics, vol. 22, no. 3, pp. 525-529, 2013,
Citation: HU Yanyan and ZHOU Donghua, “Time-varying Bias Estimation for Asynchronous Multi-sensor Multi-target Tracking Systems Using STF,” Chinese Journal of Electronics, vol. 22, no. 3, pp. 525-529, 2013,

Time-varying Bias Estimation for Asynchronous Multi-sensor Multi-target Tracking Systems Using STF

Funds:  This work is supported by the National Basic Research Program of China (973 Program) (No.2010CB731800, No.2009CB320602) and the National Natural Science Foundation of China (No.61210012, No.61021063, No.61290324).
  • Received Date: 2011-05-01
  • Rev Recd Date: 2012-05-01
  • Publish Date: 2013-06-15
  • Time-varying bias estimation problem was studied for multi-target tracking systems with asynchronous sensors without knowing bias dynamics. We considered general situations, where the number of sensors was arbitrary as well as their sampling rates and initial sampling instants. A two-layer fusion structure was adopted. For each target, a pseudo-measurement of sensor bias was generated by fusing sensor measurements of this target. To make the pseudo-measurement decoupled from the target state, the fusion coefficient matrix was determined to be a basis for the left null space of an augmented observation matrix. The bias estimation algorithm was proposed based on the Strong tracking filter (STF) by fusing pseudomeasurements. The proposed algorithm makes use of all available sensor information, has strong tracking ability to abrupt changes, and avoids the matrix inversion for large dimensional matrices. Finally, the performance of the proposed algorithm is illustrated by the numerical simulation.
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  • Y. Bar-Shalom and X.R. Li, Multitarget-Multisensor Tracking: Principles and Techniques, NewOrleans, LA: University of New Orleans, 1995.
    M. Lei and C.Z. Han, “Unifies maneuvering model for target tracking by using range-rate measurement”, Chinese Journal of Electronics, Vol.17, No.3, pp.551-557, 2008.
    D.L. Hall and J. Llinas, Handbook of Multisensor Data Fusion, Boca Raton, FL: CRC press, 2001.
    C.L. Wen, Q.B. Ge and X.F. Tang, “Kalman filtering in a bandwidth constrained sensor network”, Chinese Journal of Electronics, Vol.18, No.4. pp.713-718, 2009.
    M.P. Dana, “Registration: A prerequisite for multiple sensor tracking”, in Multitarge-Multisensot Tracking: Advanced Apptications, Y. Bar-Shalom, Ed. Norwood, MA: Artech House, pp.155-185, 1990.
    N. Nabaa and R.H. Bishop, “Solution to a multisensor tracking problem with sensor registration error”, IEEE Transactions on Aerospace and Electronic Systems, Vol.35, No.1, pp.354-363, 1999.
    W. Li and H. Leung, “Simultaneous registration and fusion of multiple dissimilar sensors for cooperative driving”, IEEE Transactions on Intelligent Transportation Systems, Vol.5, No.2, pp.84-98, 2004.
    X. Lin, Y. Bar-Shalom and T. Kirubarajan, “Multisensormultitarget bias estimation for general asynchronous sensors”,IEE Transactions on Aerospace and Electronic Systems, Vol.41, No.3, pp.899-921, 2005.
    Y.Q. Qi, Z.L. Jing and S.Q. Hu, “General solution for asynchronous sensors bias estimation”, 11th International Conference on Information Fusion, Cologrne, Germany, pp.258-264, 2009.
    M. Bai, D.H. Zhou and H. Schwarz, “Identification of generalized friction for an experimental planar two-link flexible manipulator using strong tracking filter”, IEEE Transactions on Robotics and Automation, Vol.15, No.2, pp.362-369, 1999.
    D.H. Zhou and P.M. Frank, “Fault diagnostics and fault tolerant control”, IEEE Transactions on Aerospace and Eletronic Systems, Vol.34, No.2, pp.420-427, 1998.
    M. Bai, D.H. Zhou and H. Schwarz, “Adaptive augmented state feedback control for an experimentalplanar two-link flexible manipulator”, IEEE Transactions on Robotics and Automation, Vol.14, No.6, pp.940-950, 1998.
    Y. Bar-Shalom, “Airbrne GMTI radar position bias estimation using static-rotator targets of opportunity”, IEEE Transactions on Aerospace and Electronic Systems, Vol.37, No.2, pp.695-699, 2001.
    K. Kastella, B. Yeary, T. Zadra, R. Brouillard and E. Frangione, “Bias modeling and estimation for GMTI applications”, 3th International Conference on Information Fusion, Paris, France, pp.TUC1/7-12, 2000.
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