Robust Non Parametric CFAR Detector in Compound Gaussian Clutter in the Presence of Thermal Noise and Interfering Targets

  • Nouh Guidoum
  • Faouzi SoltaniEmail author
  • Khaled Zebiri
  • Amar Mezache
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10884)


The Concept of constant false alarm rate CFAR detection is usually a requirement for any modern radar system. This paper proposes a generalization of a robust CFAR detector to account for the presence of thermal noise and interfering targets. We show via simulation results that the proposed detector keeps the CFAR property for a class of compound Gaussian clutter, namely: the K distribution, the Generalized Pareto distribution and the Compound Inverse Gaussian distribution. The results obtained show that the probability of false alarm is almost independent of the clutter parameter for all the cases studied.


CFAR Compound Gaussian Robust detection Interfering targets Thermal noise 


  1. 1.
    Conte, E., Maio, A.D.: Statistical analysis of real clutter at different range resolutions. IEEE Trans. AES 40(3), 903–918 (2004)Google Scholar
  2. 2.
    Billingsley, J.B.: Low Angle Radar Land Clutter. William Andrew Publishing, Inc., Norwich (2002)Google Scholar
  3. 3.
    Weinberg, G.V., Glenny, V.G.: Enhancing Goldstein’s log-t detector in Pareto distributed clutter. IEEE Trans. Aerosp. Electron. Syst. 53, 1035–1044 (2017)CrossRefGoogle Scholar
  4. 4.
    Weber, P., Haykin, S.: Ordered statistic CFAR processing for two-parameter distributions with variable skewness. IEEE Trans. AES AES–21, 819–821 (1985)Google Scholar
  5. 5.
    Goldstein, G.B.: False-alarm regulation in log-normal and Weibull clutter. IEEE Trans. Aerosp. Electron. Syst. AES–9, 84–92 (1973)CrossRefGoogle Scholar
  6. 6.
    Watts, S.: The performance of cell-averaging CFAR systems in sea clutterGoogle Scholar
  7. 7.
    Zebiri, K., Soltani, F., Mezache, A.: Robust non-parametric CFAR detector in compound Gaussian clutter. In: 3rd International Conference on Frontiers of Signal Processing, 6–8 September 2017, Paris, France (2017)Google Scholar
  8. 8.
    Ward, K.D., Tough, R.J.A., Watts, S.: Sea Clutter: Scattering, the K-distribution and Radar Performance, 2nd edn. Institution of Engineering and Technology, London (2013)Google Scholar
  9. 9.
    Mezache, A., Chalabi, I., Soltani, F., Sahed, M.: Estimating the Pareto plus noise distribution parameters using non-integer order moments and [zlog(z)] approaches. IET Radar Sonar Navig. 10(1), 192–204 (2016)CrossRefGoogle Scholar
  10. 10.
    Mezache, A., Soltani, F., Sahed, M., Chalabi, I.: Model for non-Rayleigh clutter amplitudes using compound inverse Gaussian distribution: an experimental analysis. IEEE Trans. Aerosp. Electron. Syst. 51, 142–153 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Nouh Guidoum
    • 1
  • Faouzi Soltani
    • 1
    Email author
  • Khaled Zebiri
    • 1
  • Amar Mezache
    • 2
  1. 1.Laboratoire Signaux et Systèmes de Communication, Département d’ElectroniqueUniversité des Frères Mentouri ConstantineConstantineAlgeria
  2. 2.Département d’ElectroniqueUniversité Mohamed BoudiafM’SilaAlgeria

Personalised recommendations