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Radar CFAR detection for multiple-targets situations for Weibull and log-normal distributed clutter

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Abstract

In the presence of Weibull clutter, the development of sliding window detection processes, based on scale and power invariant distributions, has been extensively examined. This involves the selection of two functions labeled as scale-invariant and secondary CRP (clutter range profile) functions. However, due to the presence of outliers, existing CFAR (constant false alarm rate) algorithms show remarkable CFAR losses. We resort in this work to the practice of a suitable choice of these two functions in order to have a new decision rule with immunity against interfering targets. To do this, a quadruple-order statistics-based CFAR detection algorithm with different four-order statistics are proposed in the presence of log-normal and Weibull clutter disturbances. Via Monte Carlo simulations, the analysis of the false alarm regulation of the proposed detector is studied showing its robustness with respect to clutter parameters. Moreover, for comparison purposes with existing CFAR algorithms, simulated results indicate that lowest CFAR losses can be obtained by the proposed quadruple-order statistics named WHWH-CFAR (Weber–Haykin-Weber–Haykin) in the presence of strong interfering targets. IPIX real data are also performed to test the validity of the proposed detector.

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References

  1. Weinberg, G.V.: On the construction of CFAR decision rules via transformations. IEEE Trans. Geosci. Remote Sens. 55(2), 1140–1146 (2016)

    Article  Google Scholar 

  2. Barkat, M.: Signal detection and estimation, 2nd edn. Artech House, Norwood, MA (2005)

    Google Scholar 

  3. Weiner, M.A.: Binary integration of fluctuating targets. IEEE Trans. Aerosp. Elect. Syst. 27(1), 11–17 (1991)

    Article  Google Scholar 

  4. Chwartz, M.: A coincidence procedure for signal detection. IRE Trans. Inf. 2(4), 135–139 (1956)

    Article  Google Scholar 

  5. Tang, S., Zhu, J., Xie, Y.: Radar CFAR processing and design for hybrid Weibull and Log-Normal clutters. Paper Presented at the IEEE RadarCon (RADAR), Kansas city, MO, USA, May 23–27 (2011)

  6. Bentoumi, A., Mezache, A., Kerbaà, T.: Performance of non-parametric CFAR detectors in log-normal and K radar clutter. Paper Presented at the (CISTEM), International Conference of on Electrical Sciences and Technologies in Maghreb, Algiers, Algeria, pp 28–31 (2018)

  7. Pourmottaghi, A., Gazor, S.: A CFAR detector in a Non homogenous Weibull Clutter. IEEE Trans. Aerosp. Elect. Syst. 48(2), 1747–1758 (2012)

    Article  Google Scholar 

  8. Weinberg, G.V., Kyprianou, R.: Optimized binary integration with order statistic CFAR in Pareto distributed Clutter. Dig. Sig. Process. 42, 50–60 (2015)

    Article  Google Scholar 

  9. Weinberg, G.V.: Assessing the pareto fit to high resolution high grazing angle sea clutter. Elect. Lett. 47(8), 516–517 (2011)

    Article  Google Scholar 

  10. Finn, H. M.: Adaptive detection in clutter. Proc. Natl. Elect. Conf., pp. 562–567 (1966)

  11. Finn, H.M., Johnson, R.S.: Adaptive detection mode with threshold control as function of spatially sampled clutter level estimates. RCA Rev. 29, 414–463 (1968)

    Google Scholar 

  12. Goldstein, G.B.: False-alarm regulation in log-normal and Weibull clutter. IEEE Trans. Aerosp. Elect. Syst. 9(1), 84–92 (1973)

    Article  Google Scholar 

  13. Weber, P., Haykin, S.: Ordered statistic CFAR processing for two-parameter distributions with variable skewness. IEEE Trans. Aerosp. Elect. Syst. 21(6), 819–821 (1985)

    Article  Google Scholar 

  14. Weinberg, G.V.: Geometric mean switching constant false alarm rate detector. Dig. Sig. Process. 69, 1–10 (2017)

    Article  Google Scholar 

  15. Weinberg, G.V., Alexopoulos, A.: Analysis of a dual order statistic constant false alarm rate detector. IEEE Trans. Aerosp. Elect. Syst. 52(5), 2567–2574 (2016)

    Article  Google Scholar 

  16. Weinberg, G.V., Glenny, V.G.: Enhancing goldstein’s log-t detector in pareto distributed clutter. IEEE Trans. Aerosp. Elect. Syst. 53(2), 1035–1044 (2017)

    Article  Google Scholar 

  17. Weinberg, G.V.: Trimmed geometric mean order statistic CFAR detector for Pareto distributed clutter. Sig. Image Video Process. 12(4), 651–657 (2018)

    Article  Google Scholar 

  18. Weinberg, G.V., Bateman, L., Hayden, P.: Development of non-coherent CFAR detection processes in Weibull background. Dig. Sig. Process. 75, 96–106 (2018)

    Article  MathSciNet  Google Scholar 

  19. Mezache, A., Soltani, F.: Threshold optimization of decentralized CFAR Detection in Weibull clutter using genetic algorithms. Sig. Image Video Process. 2, 1–7 (2008)

    Article  Google Scholar 

  20. Mezache, A., Bentoumi, A., Sahed, M.: Parameter estimation for compound-Gaussian clutter with inverse-Gaussian texture. IET Radar Sonar Navig. 11(4), 586–596 (2017)

    Article  Google Scholar 

  21. Chung, P., Roberts, W., Bohme, J.: Recursive K-distribution parameters estimation. IEEE Trans. Sig. Process. 53(2), 397–402 (2005)

    Article  MathSciNet  Google Scholar 

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Correspondence to Khaled Zebiri.

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Zebiri, K., Mezache, A. Radar CFAR detection for multiple-targets situations for Weibull and log-normal distributed clutter. SIViP 15, 1671–1678 (2021). https://doi.org/10.1007/s11760-021-01905-6

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  • DOI: https://doi.org/10.1007/s11760-021-01905-6

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