Multitarget analysis of CFAR detection of partially-correlated χ2 targets

Authors

  • Mohamed Bakry El Mashade Al-Azhar University, Egypt

DOI:

https://doi.org/10.3103/S0735272716010015

Keywords:

CFAR radar schemes, multipulse-detection, Swerling fluctuation models, partially-correlated targets, multitarget environment

Abstract

The goal of this paper is to treat the problem of detecting the partially-correlated χ2 fluctuating targets with two and four degrees of freedom. We analyze the detection performance in general terms of the more generalized version, which is known as GTM, of the CFAR processors when the operating environment is contaminated with outlying target returns and the radar receiver carries its processing based on post-detection integration of M exponentially correlated pulses. Analytical formulas for the detection and false alarm probabilities are derived, in the absence as well as in the presence of spurious targets which are assumed to be moderately fluctuating following χ2 target models. A performance assessment by numerous numerical examples, which has considered the role that each parameter can play in the processor performance, is given. The obtained results show that the processor performance enhances, for weak SNR of the primary target, as the correlation coefficient ρs increases and this occurs either in the absence or in the presence of extraneous targets. As the strength of the target return increases, the processor tends to invert its behavior. The well-known Swerling models embrace the correlated target cases in the situation where the correlation among the target returns follows χ2 fluctuation models with two and four degrees of freedom and this behavior is common for all GTM based detectors.

References

WANG, W.-Q. (ed.), Radar Systems: Technology, Principles and Applications. Nova Science Pub. Inc., 2013, ISBN-10: 1624178723.

ZHAO, L.; LIU, W.; FU, J.S.; SEOW, S. YONG; WU, X. Two new CFAR detectors based on OR-algorithm and AND-algorithm. Proc. of Int. Conf. on Research and Development, SCOReD, 2001, KL, Malaysia, 2001, p.31-34.

EL MASHADE, M.B. Analysis of the censored-mean level CFAR processor in multiple target and nonuniform clutter. IEE Proc. Radar, Sonar Navig., Oct. 1995, v.142, n.5, p.259-266, DOI: http://dx.doi.org/10.1049/ip-rsn:19951985.

EL MASHADE, M.B. Detection performance of the trimmed-mean CFAR processor with noncoherent integration. IEE Proc. Radar, Sonar Navig., Feb. 1995, v.142, n.1, p.18-24, DOI: http://dx.doi.org/10.1049/ip-rsn:19951626.

SWERLING, PETER. Radar probabilitity of detection for some additional fluctuating target cases. IEEE Trans. Aerosp. Electron. Syst., Apr. 1997, v.33, n.2, p.698-709, DOI: http://dx.doi.org/10.1109/7.588492.

HAMMOUDI, Z.; SOLTANI, F. Distributed CA-CFAR and OS-CFAR detection using fuzzy spaces and fuzzy fusion rules. IEE Proc. Radar Sonar Navig., Jun. 2004, v.151, n.3, p.135-142, DOI: http://dx.doi.org/10.1049/ip-rsn:20040560.

EL MASHADE, M.B. Multipulse analysis of the generalized trimmed-mean CFAR detector in nonhomogeneous background environments. AEU, Aug. 1998, v.52, n.4, p.249-260.

EL MASHADE, M.B. Target multiplicity performance analysis of radar CFAR detection techniques for partially correlated chi-square targets. AEU, Apr. 2002, v.56, n.2, p.84-98, DOI: http://dx.doi.org/10.1078/1434-8411-54100077.

FARROUKI, ATEF; BARKAT, MOURAD. Automatic censored mean level detector using a variability-based censoring with non-coherent integration. Signal Processing, Jun. 2007, v.87, n.6, p.1462-1473, DOI: http://dx.doi.org/10.1016/j.sigpro.2006.12.012.

ZHAO, LEI; LIU, WEIXIAN; WU, XIN; FU, J.S. A novel approach for CFAR processors design. Proc. of IEEE Int. Radar Conf., 1-3 May 2001, Atlanta, GA. IEEE, 2001, p.284-288, DOI: http://dx.doi.org/10.1109/NRC.2001.922992.

EL MASHADE, M.B. Analysis of adaptive detection of moderately fluctuating radar targets in target multiplicity environments. J. Franklin Inst., Aug. 2011, v.348, n.6, p.941-972, DOI: http://dx.doi.org/10.1016/j.jfranklin.2011.03.004.

EL MASHADE, M.B. Target-multiplicity analysis of CML processor for partially-correlated χ2 targets. Int. J. Aerosp. Sci., 2012, v.1, n.5, p.92-106, DOI: http://dx.doi.org/10.5923/j.aerospace.20120105.02.

EL MASHADE, M.B. Multiple-target analysis of adaptive detection of partially correlated χ2 targets. Int. J. Space Sci. Eng., 2013, v.1, n.2, p.142-176, DOI: http://dx.doi.org/10.1504/IJSPACESE.2013.054450.

EL MASHADE, M.B. Analytical performance evaluation of optimum detection of χ2 fluctuating targets with M-integrated pulses. Electrical and Electronic Engineering, 2011, v.1, n.2, p.93-111, DOI: http://dx.doi.org/10.5923/j.eee.20110102.15.

EL MASHADE, M.B. Detection analysis of linearly combined order statistic CFAR algorithm in nonhomogeneous background environments. Signal Processing, Jul. 1998, v.68, n.1, p.59-71, DOI: http://dx.doi.org/10.1016/S0165-1684(98)00057-7.

EL MASHADE, M.B. Performance comparison of a linearly combined ordered-statistic detectors under postdetection integration and nonhomogeneous situations. J. Electron. (China), Sept. 2006, v.23, n.5, p.698-707, DOI: http://dx.doi.org/10.1007/s11767-004-0213-0.

EL MASHADE, M.B. Analysis of CFAR detection of partially-correlated X2 targets in the presence of interferers. Majlesi J. Electrical Eng., Sept. 2013, v.7, n.3, p.43-58, http://mjee.iaumajlesi.ac.ir/index/index.php/ee/article/view/880.

Published

2016-01-21

Issue

Section

Research Articles