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Hierarchical Track–Before–Detect Algorithm for Tracking of Amplitude Modulated Signals

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Image Processing and Communications Challenges 3

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 102))

Summary

In the paper Track–Before–Detect (TBD) algorithm for tracking a low–signal objects with amplitude modulated signal is proposed. Direct application of TBD algorithms is not sufficient for such case due to accumulative approach. This signal has a zero mean value and cannot be processed directly. The proposed algorithm is based on applications of two different TBD algorithms. The first is the directional IIR filter that works as a velocity filter as a part of the noncoherent demodulator. The second TBD algorithm is the recurrent Spatio–Temporal TBD that support trajectory switching using Markov’s matrix. Numerical experiments (Monte Carlo tests) for point target are used for verification of the proposed solution.

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References

  1. Blackman, S.S., Popoli, R.: Design and Analysis of Modern Tracking Systems. Artech House, Boston (1999)

    MATH  Google Scholar 

  2. Bar–Shalom, Y.: Multitarget–Multisensor Tracking: Applications and Advances, vol. II. Artech House, Boston (1992)

    Google Scholar 

  3. Brookner, E.: Tracking and Kalman Filtering Made Easy. Willey–Interscience, Hoboken (1998)

    Book  Google Scholar 

  4. Kalman, R.E.: A New Approach to Linear Filtering and Prediction Problems. Transactions of the ASME–Journal of Basic Engineering 82, Series D, 35–46 (1960)

    Google Scholar 

  5. Stone, L.D., Barlow, C.A., Corwin, T.L.: Bayesian Multiple Target Tracking. Artech House, Boston (1999)

    MATH  Google Scholar 

  6. Blackman, S.: Multiple–Target Tracking with Radar Applications. Artech House, Boston (1986)

    Google Scholar 

  7. Dijk, J., van Eekeren, A.W.M., Schutte, K., de Lange, D.J.J., van Vliet, L.J.: Superresolution reconstruction for moving point target detection. Optical Engineering 47(9) (2008)

    Google Scholar 

  8. Liggins, M.E., Llinas, J., Hall, D.L.: Handbook of Multisensor Data Fusion. CRC Press, Boca Raton (2008)

    Book  Google Scholar 

  9. Jain, L.C., Ichalkaranje, N.S., Tonfoni, G. (eds.): Advances in Intelligent Systems for Defence. World Scientific, Singapore (2002)

    Google Scholar 

  10. Mazurek, P.: Optimization of Track–Before–Detect Systems with Decimation for GPGPU. Pomiary Automatyka Kontrola 56(12), 1523–1525 (2010)

    Google Scholar 

  11. Mazurek, P.: Implementation of spatio–temporal Track–Before–Detect algorithm using GPU. Pomiary Automatyka Kontrola 55(8), 657–659 (2009)

    Google Scholar 

  12. Boers, Y., Ehlers, F., Koch, W., Luginbuhl, T., Stone, L.D., Streit, R.L. (eds.): Track Before Detect Algorithm. EURASIP Journal on Advances in Signal Processing, Hindawi (2008)

    Google Scholar 

  13. Doucet, A., de Freitas, N., Gordon, N., Smith, A. (eds.): Sequential Monte Carlo Methods in Practice. Springer, Heidelberg (2001)

    MATH  Google Scholar 

  14. Ristic, B., Arulampalam, S., Gordon, N.: Beyound the Kalman Filter: Particle Filters for Tracking Applications. Artech House, Boston (2004)

    Google Scholar 

  15. Mazurek, P.: Optimization of bayesian Track–Before–Detect algorithms for GPGPUs implementations. Electrical Review R 86(7), 187–189 (2010)

    Google Scholar 

  16. Mazurek, P.: Direct visualization methods for Track–Before–Detect algorithms. Poznan University of Technology Academic Journals – Electrical Engineering 59, 25–34 (2009)

    Google Scholar 

  17. Goertzel, G.: An Algorithm for the Estimation of Finite Trigonometric Series. American Mathematical Monthly 65(1), 34–35 (1958)

    Article  MathSciNet  MATH  Google Scholar 

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Mazurek, P. (2011). Hierarchical Track–Before–Detect Algorithm for Tracking of Amplitude Modulated Signals. In: Choraś, R.S. (eds) Image Processing and Communications Challenges 3. Advances in Intelligent and Soft Computing, vol 102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23154-4_56

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  • DOI: https://doi.org/10.1007/978-3-642-23154-4_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23153-7

  • Online ISBN: 978-3-642-23154-4

  • eBook Packages: EngineeringEngineering (R0)

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