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Clutter map CFAR detector based on maximal resolution cell

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Abstract

In order to improve the detection performance of clutter map constant false alarm rate (CFAR) detectors in multiple persisting targets situation, a clutter map CFAR (CM-CFAR) detector based on the maximal resolution cell (CM/MRC-CFAR) is proposed in this paper. In the CM/MRC-CFAR detector, at each scan, a comparison threshold is computed by multiplying the amplitude of the maximal resolution cell (MRC) in the map cell by a scaling factor. Then, the number of the left resolution cells, whose amplitudes are smaller than the comparison threshold, is counted and compared with a threshold integer. Based on the comparison result, proper resolution cells are selected to update the detection threshold. The detection probability of CM/MRC-CFAR in both homogeneous and multiple persisting targets situations is derived in a closed-form expression. The detection performance of CM/MRC-CFAR is evaluated in various environments and compared with other CM-CFAR detectors. CM/MRC-CFAR exhibits a very low CFAR loss in a homogeneous environment and achieves a robust detection performance in multiple persisting targets situations. Since no ranking is required except searching for the MRC, the computation load of CM/MRC-CFAR is low, and it is easy to implement the detector in radar systems in practice.

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References

  1. Skolnik, M.I.: Introduction to Radar Systems, 3rd edn. McGraw-hill Book Company, NY (2001)

    Google Scholar 

  2. Khalighi, M.A., Bastani, M.H.: Adaptive CFAR processor for nonhomogeneous environments. IEEE Trans. Aerosp. Electron. Syst. 36(3), 889–897 (2000)

    Article  Google Scholar 

  3. Weiss, M.: Analysis of some modified cell-averaging CFAR processors in multiple-target situations. IEEE Trans. Aerosp. Electron. Syst. 18(1), 102–114 (1982)

    Article  Google Scholar 

  4. Naldi, M.: False alarm control and self-masking avoidance by a biparametric clutter map in a mixed interference environment. IEE Proc.-Radar Sonar Navig. 146(4), 195–200 (1999)

    Article  Google Scholar 

  5. Meng, X.W.: Performance analysis of Nitzberg’s clutter map for Weibull distribution. Digit. Signal Process. 20(3), 916–922 (2010)

    Google Scholar 

  6. Hammoudi, Z., Soltani, F.: Distributed CA-CFAR and OS-CFAR detection using fuzzy spaces and fuzzy fusion rules. IEE Radar Sonar Navig. 151(3), 135–142 (2004)

    Article  Google Scholar 

  7. Maio, A.De, Farina, A., Foglia, G.: Design and experimental validation of knowledge-based constant false alarm rate detectors. IET Radar Sonar Navig. 1(4), 308–316 (2007)

    Article  Google Scholar 

  8. Gandhi, P.P., Kassam, S.A.: Analysis of CFAR processors in nonhomogeneous background. IEEE Trans. Aerosp. Electron. Syst. 24(4), 427–444 (1988)

    Article  Google Scholar 

  9. Cao, T.V.: Constant false-alarm rate algorithm based on test cell information. IET Radar Sonar Navig. 2(3), 200–213 (2008)

    Article  Google Scholar 

  10. Finn, H.M.: A CFAR design for a window spanning two clutter fields. IEEE Trans. Aerosp. Electron. Syst. 22(2), 155–169 (1986)

    Article  Google Scholar 

  11. Meng, X.W.: Performance analysis of ordered-statistic greatest of-constant false alarm rate with binary integration for M-sweeps. IET Radar Sonar Navig. 4(1), 37–48 (2010)

  12. Shnidman, D.A.: Radar detection in clutter. IEEE Trans. Aerosp. Electron. Syst. 41(3), 1056–1067 (2005)

    Google Scholar 

  13. Smith, M.E., Varshney, P.K.: Intelligent CFAR processor based on data variability. IEEE Trans. Aerosp. Electron. Syst. 36(3), 837–847 (2000)

    Article  Google Scholar 

  14. Farrouki, A., Barkat, M.: Automatic censoring CFAR detector based on ordered data variability for nonhomogeneous environments. IEE Radar Sonar Navig. 152(1), 43–51 (2005)

    Article  Google Scholar 

  15. Lops, M., Orsini, M.: Scan-by-scan averaging CFAR. IEE Proc. F Radar Signal Process. 136(6), 249–254 (1989)

    Article  Google Scholar 

  16. Shan, T., Tao, R., Wang, Y., et al.: Novel clutter map CFAR algorithm with amplitude limiter. J. Syst. Eng. Electron. 15(3), 262–265 (2004)

    Google Scholar 

  17. Hamadouche, M., Barakat, M., Khodja, M.: Analysis of the clutter map CFAR in Weibull clutter. Signal Process. 80(1), 117–123 (2000)

    Google Scholar 

  18. Nitzberg, R.: Clutter map CFAR analysis. IEEE Trans. Aerosp. Electron. Syst. 22(4), 419–421 (1986)

    Article  Google Scholar 

  19. Levanon, N.: Numerically efficient calculations of clutter map CFAR performance. IEEE Trans. Aerosp. Electron. Syst. 23(6), 813–814 (1987)

    Article  Google Scholar 

  20. Conte, E., Lops, M.: Clutter-map CFAR detection for range-spread targets in non-Gaussian clutter. Part I: system design. IEEE Trans. Aerosp. Electron. Syst. 33(2), 432–443 (1997)

    Article  Google Scholar 

  21. Shan, T., Tao, R., Wang, Y., et al.: Performance of order statistic clutter map CFAR. In: Proceeding of International Conference on Signal Processing, pp. 1572–1575 (2002)

  22. Lops, M.: Hybrid clutter-map/L-CFAR procedure for clutter rejection in nonhomogeneous environment. IEE Proc.-Radar Sonar Navig. 143(4), 239–245 (1996)

    Article  Google Scholar 

  23. Gurakan, B., Candan, C., Ciloglu, T.: CFAR processing with switching exponential smoothers for nonhomogeneous environments. Digit. Signal Process. 22, 407–416 (2012)

    Article  MathSciNet  Google Scholar 

  24. Conte, E., Lops, M., Tulino, A.M.: Hybrid procedure for CFAR in non-Gaussian clutter. IEE Proc.-Radar Sonar Navig. 144(6), 361–369 (1997)

    Article  Google Scholar 

  25. Conte, E., Bisceglie, M.D., Lops, M.: Clutter-map CFAR detection for range-spread targets in non-Gaussian clutter. Part II: performance assessment. IEEE Trans. Aerosp. Electron. Syst. 33(2), 444–455 (1997)

    Article  Google Scholar 

  26. Arnold, B.C., Balakrishnan, N., Nararaja, H.N.: A First Course in Order Statistics (2008, SIAM Edition)

Download references

Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under grant 11273017.

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Correspondence to Ren-li Zhang.

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Zhang, Rl., Sheng, Wx., Ma, Xf. et al. Clutter map CFAR detector based on maximal resolution cell. SIViP 9, 1151–1162 (2015). https://doi.org/10.1007/s11760-013-0544-0

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  • DOI: https://doi.org/10.1007/s11760-013-0544-0

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