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New optimal algorithm of data association for multi-passive-sensor location system

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Abstract

In dense target and false detection scenario of four time difference of arrival (TDOA) for multi-passive-sensor location system, the global optimal data association algorithm has to be adopted. In view of the heavy calculation burden of the traditional optimal assignment algorithm, this paper proposes a new global optimal assignment algorithm and a 2-stage association algorithm based on a statistic test. Compared with the traditional optimal algorithm, the new optimal algorithm avoids the complicated operations for finding the target position before we calculate association cost; hence, much of the procedure time is saved. In the 2-stage association algorithm, a large number of false location points are eliminated from candidate associations in advance. Therefore, the operation is further decreased, and the correct data association probability is improved in varying degrees. Both the complexity analyses and simulation results can verify the effectiveness of the new algorithms.

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References

  1. Yeddanapudi M, Deb S, Pattipati K R, et al. A generalized S-D assignment algorithm for multisensor-multitarget state estimation. IEEE Trans Aerospace Elect Syst, 1997, 33(2): 523–537

    Article  Google Scholar 

  2. Pattipati K R, Deb S, Bar-shalom Y, et al. A new relaxation algorithm and passive sensor data association. IEEE Trans Autom Contr, 1992, 37(1): 198–213

    Article  MATH  Google Scholar 

  3. Deb S, Pattipati K R, Bar-shalom Y. A multisensor-multitarget data association algorithm for heterogeneous sensors. IEEE Trans Autom Contr, 1993, 29(2): 560–568

    Google Scholar 

  4. Wang C, Li S H, Huang H. Study on algorithm of data association in multi-passive-sensor multi-target system. Acta Electr Sin (in Chinese), 2002, 30(12): 1857–1860

    Google Scholar 

  5. He Y, Wang G H, Lu D J, et al. Multisensor Information Fusion with Applications (in Chinese). Beijing: Publishing House of Electronics Industry, 2000

    Google Scholar 

  6. Chummun M R, Kirubarajar T, Pattipati K R, et al. Fast data association using multidimensional assignment with clustering. IEEE Trans Aerospace Elect Syst, 2001, 37: 898–913

    Article  Google Scholar 

  7. Zhou L, He Y, Wang X J. Application of four-dimension assignment algorithm of data association in distributed passive-sensor system. LNCS, 2005, 3514: 812–819

    Google Scholar 

  8. Bertsekas D P. The auction algorithm: A distributed relaxation method for the assignment problem. Annals Operat Res, 1988, 14: 105–123

    Article  MATH  Google Scholar 

  9. Ma Z H. Operational Research and the Optimal Theorem (in Chinese). Beijing: Publishing House of Tsinghua University, 1998

    Google Scholar 

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Correspondence to Zhou Li.

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Supported by the National Natural Science Foundation of China (Grant Nos. 60172033, 60672139 and 60672140), the Excellent Ph. D. Paper Author Foundation of China (Grant No. 200237), and the Natural Science Foundation of Shandong Province (Grant No. 2005ZX01)

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Zhou, L., He, Y. & Zhang, W. New optimal algorithm of data association for multi-passive-sensor location system. SCI CHINA SER F 50, 600–608 (2007). https://doi.org/10.1007/s11432-007-0042-5

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  • DOI: https://doi.org/10.1007/s11432-007-0042-5

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