An EVI-ASD-CFAR Processor in a Pareto background and multiple target situations

This paper investigates the problem of automatic target detection in a Pareto background under multiple target situations. The number of interfering targets is assumed to be unknown. We derive the Enhanced Variability Index Automatic Selection and Detection Constant False Alarm Rate (EVI-ASD-CFAR) Processor. This latter selects and matches dynamically the suitable detector among the Geometric Mean (GM)-CFAR, Greatest Of(GO)-CFAR and Trimmed Mean (TM)-CFAR. The unknown background level is then estimated and set to the corresponding threshold. The detection performances of the proposed processor are assessed via Monte Carlo simulations.

[1]  Faouzi Soltani,et al.  A generalized switching CFAR processor based on test cell statistics , 2009, Signal Image Video Process..

[2]  G. Trunk.  Range Resolution of Targets Using Automatic Detectors , 1978, IEEE Transactions on Aerospace and Electronic Systems.

[3]  G. Trunk.  Radar Properties of Non-Rayleigh Sea Clutter , 1972, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Tuan Vu Cao,et al.  Constant false-alarm rate algorithm based on test cell information , 2008 .

[5]  Zoheir Hammoudi,et al.  Distributed IVI-CFAR detection in non-homogeneous environments , 2004, Signal Process..

[6]  N. Detouche,et al.  Extensive Monte Carlo simulations for performance comparison of three non-coherent integrations using Log-t-CFAR detection against Weibull clutter , 2012, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT).

[7]  S. D. Himonas,et al.  Automatic censored CFAR detection for nonhomogeneous environments , 1992 .

[8]  K. Ward.  Compound representation of high resolution sea clutter , 1980 .

[9]  Saeed Gazor,et al.  A CFAR Detector in a Nonhomogenous Weibull Clutter , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[10]  Graham V. Weinberg.  Constant False Alarm Rate Detection in Pareto Distributed Clutter: Further Results and Optimality Issues , 2014 .

[11]  Graham V. Weinberg.  Formulation of a generalised switching CFAR with application to X-band maritime surveillance radar , 2015, SpringerPlus.

[12]  M. Barkat,et al.  Automatic censoring CFAR detector based on ordered data variability for nonhomogeneous environments , 2005 .

[13]  V. Hansen,et al.  Detectability Loss Due to "Greatest Of" Selection in a Cell-Averaging CFAR , 1980, IEEE Transactions on Aerospace and Electronic Systems.

[14]  Pramod K. Varshney,et al.  Intelligent CFAR processor based on data variability , 2000, IEEE Trans. Aerosp. Electron. Syst..

[15]  John Rickard,et al.  Adaptive Detection Algorithms for Multiple-Target Situations , 1977, IEEE Transactions on Aerospace and Electronic Systems.

[16]  George A. Lampropoulos,et al.  A new and robust CFAR detection algorithm , 1992 .

[17]  H. M. Finn,et al.  Adaptive detection mode with threshold control as a function of spatially sampled clutter level estimates , 1968 .

[18]  Xiaofeng Ma,et al.  Improved switching CFAR detector for non-homogeneous environments , 2013, Signal Process..

[19]  Amar Mezache,et al.  Trimmed Mean-based Automatic Censoring and Detection in Pareto background , 2015, 2015 4th International Conference on Electrical Engineering (ICEE).

[20]  Saleem A. Kassam,et al.  Analysis of CFAR processors in homogeneous background , 1988 .