Open Access Open Access  Restricted Access Subscription Access
Monopulse P_fa rate performance of conventional CFAR processors and their developed versions at clutter edge of 5 dB

Performance amelioration of standard variants of adaptive schemes operating in heterogeneous environment

Mohamed Bakry El Mashade


The ruggedness of emerging single adaptive approach that performs well in all types of operating conditions has led to the development of composite adaptive strategy. In this regard, the fusion of particular decisions of single adaptive schemes through suitable fusion rules can provide a better final detection. Particularly, the fusion of cell-averaging (CA), ordered statistics (OS) and trimmed-mean (TM) procedures can enhance the overall detection performance. Our goal in this paper is to analyze this developed model when the operating environment is heterogeneous. A χ2-distribution with two- and four-degrees of freedom is assumed for the fluctuation of primary and secondary extraneous targets. A closed form processor performance is derived for single pulse detection. The results show that for the non-homogeneous background the new approach is more practical. Particularly in multitarget situations, it exhibits higher robustness as compared to the CA, OS, or TM architectures. Additionally, the novel strategy has a homogeneous performance that surpasses performance of the classical Neyman-Pearson (N-P) detector, which can be employed as a yardstick for the analysis of different techniques in the CFAR world.


conventional CFAR detector; monopulse detection; Neyman-Pearson detector; χ2-distribution with 2-degrees of freedom; Swerling model; heterogeneous environment

Full Text:



A. R. Elias-Fusté, A. Broquetas-Ibars, J. P. Antequera, and J. C. M. Yuste, “CFAR Data Fusion Center with Inhomogeneous Receivers,” IEEE Trans. Aerosp. Electron. Syst., vol. 28, no. 1, pp. 276–285, 1992, doi:

D. Ivkovic, M. Andric, and B. Zrnic, “Nonlinear fusion CFAR detector,” in Proceedings International Radar Symposium, 2015, doi:

M. B. El Mashade, “Monopulse detection analysis of the trimmed mean CFAR processor in nonhomogeneous situations,” IEE Proc. - Radar, Sonar Navig., vol. 143, no. 2, p. 87, 1996, doi:

L. Zhao, W. Liu, X. Wu, and J. S. Fu, “A novel approach for CFAR processors design,” in IEEE National Radar Conference - Proceedings, 2001, pp. 284–288, doi:

Y. Hu and J. Liang, “CFAR Decision Fusion Approaches in the Clustered Radar Sensor Networks Using LEACH and HEED,” Int. J. Distrib. Sens. Networks, vol. 2015, pp. 1–9, 2015, doi:

S. López-Estrada and R. Cumplido, “Fusion center with neural network for target detection in background clutter,” in Proceedings of the Mexican International Conference on Computer Science, 2005, vol. 2005, pp. 189–196, doi:

M. B. El Mashade, “Analysis of Cell-Averaging based detectors for x 2 fluctuating targets in multitarget environments,” J. Electron., vol. 23, no. 6, pp. 853–863, Nov. 2006, doi:

W. Q. Wang, Radar Systems: Technology, Principles, and Applications. Nova Science Publishers, Inc, 2013.

M. B. El Mashade, “Analytical performance evaluation of adaptive detection of fluctuating radar targets,” Radioelectron. Commun. Syst., vol. 56, no. 7, pp. 321–334, Jul. 2013, doi:

D. Ivkovic, B. Zrnic, and M. Andric, “Fusion CFAR detector in receiver of the software defined radar,” in Proc. of Int. Radar Symp., 2013.

D. Ivkovic, M. Andric, and B. Zrnic, “Nonlinear fusion CFAR detector,” in Proceedings International Radar Symposium, 2015, vol. 2015-August, pp. 481–486, doi:

D. Ivkovic, M. Andric, and B. Zrnic, “A New Model of CFAR Detector,” Frequenz, vol. 68, no. 3-4, p. 125-136, 2014. DOI:

Y. Xu, C. Hou, S. Yan, J. Li, and C. Hao, “Fuzzy statistical normalization CFAR detector for non-Rayleigh data,” IEEE Trans. Aerosp. Electron. Syst., vol. 51, no. 1, pp. 383–396, Jan. 2015, doi:

D. Ivkovic, M. Andric, and B. Zrnic, “Detection of very close targets by fusion CFAR detectors,” Sci. Tech. Rev., vol. 66, no. 3, pp. 50–57, 2016, doi:

M. B. El Mashade, “Performance Predominance of a New Strategy for CFAR Processors over the N-P Model in Detecting Four Degrees of Freedom χ2 Fluctuating Targets,” Radioelectron. Commun. Syst., vol. 61, no. 9, pp. 377–393, Sep. 2018, doi:

J. R. Machado-Fernández, N. Mojena-Hernández, and J. de la C. Bacallao-Vidal, “Evaluation of CFAR detectors performance,” Iteckne, vol. 14, no. 2, 2017, doi:

J. R. Machado-Fernández and J. D. la C. Bacallao-Vidal, “Cell Averaging CFAR Detector with Scale Factor Correction through the Method of Moments for the Log-Normal Distribution,” Cienc. e Ing. Neogranadina, vol. 28, no. 1, pp. 27–44, May 2017, doi:

M. B. El Mashade, “Heterogeneous performance analysis of the new model of CFAR detectors for partially-correlated χ2-targets,” J. Syst. Eng. Electron., vol. 29, no. 1, pp. 1–17, Feb. 2018, doi:

H. Wang, Z. Tang, Y. Zhao, Y. Chen, Z. Zhu, and Y. Zhang, “Signal Processing and Target Fusion Detection via Dual Platform Radar Cooperative Illumination,” Sensors, vol. 19, no. 24, p. 5341, Dec. 2019, doi:

© Radioelectronics and Communications Systems, 2004–2020
When you copy an active link to the material is required
ISSN 1934-8061 (Online), ISSN 0735-2727 (Print)
tel./fax +38044 204-82-31, 204-90-41