Progress In Electromagnetics Research C
ISSN: 1937-8718
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By M. B. El Mashade

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This paper is intended to the analysis of adaptive radar detectors for partially correlated χ2 targets. This important class of targets is represented by the so-called moderately fluctuating Rayleigh targets, which, when illuminated by a coherent pulse train, return a train of correlated pulses with a correlation coefficient in the range 0 < ρ < 1 (intermediate between SWII and SWI models). The detection of this type of fluctuating targets is practically of great importance. Since the CFAR detectors represent an attractive class of schemes that can be used to overcome the problem of clutter by adaptively setting their threshold based on local information of total noise power, they are commonly used to decide the presence or absence of the radar target of interest, which is of partially correlated χ2 type. In addition, the OS based algorithms are chosen to carry out this task owing to their immunity to outlying targets which may be present amongst the contents of the reference window. Moreover, since the large processing time of the single-window OS detector limits its practical applications, our scope here is to analyze the performance of OS modified versions for moderately fluctuating Rayleigh targets in nonideal situations. This analysis includes the single-window as well as the double-window OS detection schemes for the case where the radar receiver postdetection integrates M square-law detected pulses and the signal fluctuation obeys χ2 statistics with two degrees of freedom. These detectors include the mean-level (ML-), the maximum (MX-) and the minimum (MN-) OS algorithms. Exact formulas for their detection probabilities are derived, in the absence as well as in the presence of spurious targets. The primary and the secondary interfering targets are assumed to be of the moderately fluctuating Rayleigh targets. Swerling's well known cases I and II represent the cases where the signal is completely correlated and completely decorrelated, respectively, from pulse to pulse. Under the multiple-target operations, the ML-OS detector has the best homogeneous performance, the MN processor has the best multitarget performance when a cluster of radar targets appears in the reference window, while the MX scheme doesn't offer any excessive merits, neither in the absence nor in the presence of outlying targets, as expected.

M. B. El Mashade, "Performance Analysis of Os Structure of CFAR Detectors in Fluctuating Target Environments," Progress In Electromagnetics Research C, Vol. 2, 127-158, 2008.

1. Dillard, G. M., "Mean level detection of nonfluctuating signals," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-10, 795-799, Nov. 1974.

2. Rickard, J. T. and G. M. Dillard, "Adaptive detection algorithm for multiple target situations," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-13, 338-343, July 1977.

3. Nitzberg, R., "Analysis of the arithmetic mean CFAR normalizer for fluctuating targets," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-10, 44-47, Jan. 1978.

4. El Mashade, M. B., "M-sweeps exact performance analysis of OS modified versions in nonhomogeneous environments," IEICE Trans. Commun., Vol. E88-B, No. 7, 2918-2927, July 2005.

5. Rohling, H., "Radar CFAR thresholding in clutter and multiple target situations," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-19, 608-621, July 1983.

6. Kanter, I., "Exact detection probability for partially correlated Rayleigh targets," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-22, 184-196, Mar. 1986.

7. Gandhi, P. P. and S. A. Kassam, "Analysis of CFAR processors in nonhomogeneous backgrounds," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-24, 427-445, July 1988.

8. Elias-Fuste, A. R., M. G. De Mercado, and E. R. Davo, "Analysis of some modified ordered-statistic CFAR: OSGO and OSSO CFAR," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-26, 197-202, January 1990.

9. Lim, C. H. and H. S. Lee, "Performance of order-statistics CFAR detector with noncoherent integration in homogeneous situations," IEE Proceedings-F, Vol. 140, No. 5, 291-296, October 1993.

10. He, Y., "Performance of some generalized modified order-statistics CFAR detectors with automatic censoring technique in multiple target situations," IEE Proc. - Radar, Sonar Navig., Vol. 141, No. 4, 205-212, August 1994.

11. El Mashade, M. B., "Performance analysis of modified ordered statistics CFAR processors in nonhomogeneous environments," Signal Processing “ELSEVIER”, Vol. 41, 379-389, Feb. 1995.

12. Swerling, P., "Radar probability of detection for some additional fluctuating target cases," IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-33, 698-709, April 1997.

13. El Mashade, M. B., "Performance analysis of OS family of CFAR schemes with incoherent integration of M-pulses in the presence of interferers," IEE Radar, Sonar Navig., Vol. 145, No. 3, 181-190, June 1998.

14. El Mashade, M. B., "Analysis of adaptive radar systems processing M-sweeps in target multiplicity and clutter boundary environments," Signal Processing “ELSEVIER”, Vol. 67, 307-329, Aug. 1998.

15. El Mashade, M. B., "Target multiplicity performance analysis of radar CFAR detection techniques for partially correlated chisquare targets," Int. J. Electron. Commun. AEU, Vol. 56, No. 2, 84-98, April 2002.

16. El Mashade, M. B., "Analysis of cell-averaging based detectors for χ2 fluctuating targets in multitarget environments," Journal of Electronics China, Vol. 23, No. 6, 853-863, November 2006.

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