ADAPTIVE DETECTION OF STATIONARY GAUSSIAN SIGNALS AGAINST A NORMAL NOISE BACKGROUND, WITH A CONSTANT FALSE-ALARM RATE

• Дата: 2017
• Автор: Galushko, V. G.
• Формат: Стаття
• Мова: rus
• Опубліковано: Видавничий дім «Академперіодика» 2017
• Теми: target detection; false alarm rate; detection threshold; signal-to-noise ratio; cell averaging; обнаружение целей; вероятность ложной тревоги; порог обнаружения; соотношение сигнал/шум; усреднение по ячейкам; виявлення цілей; вірогідність хибної тривоги; поріг виявлення; співвідношення сигнал/шум; усереднення за комірками
• Онлайн доступ: http://rpra-journal.org.ua/index.php/ra/article/view/1271
• Назва журналу: Radio physics and radio astronomy

PACS number: 84.40.Xb Purpose: Efficiency analysis of the Cell-Averaging Constant False Alarm Rate processor (CA CFAR-processor) as applied to detection of stationary Gaussian signals against a normal noise background with unknown and/or varying from scan to scan power.Design/methodology/approach: Standard methods of the theory of optimal filtration and statistical signal processing are used to calculate the true detection probability and false-alarm rate.Findings: Analytical expressions have been derived for the scaling factor which ensures a constant level of the false-alarm rate, as well as for the true detection probability in dependence on the number of the reference cells and signal-to-noise ratio. It is shown that for efficient application of the given algorithm, the number of the reference cells should be 20 to 30, depending on the signalto-noise ratio μ. In this case, the amount of loss in the signal-tonoise ratio does not exceed 1 to 2 dB as compared with the situation where the noise power is a priori known and invariable.With  μ≥30 dB the amount of loss proves to be negligibly small and the need in adaptation vanishes.Conclusions: The results obtained testify to the efficiency of application of the CA CFAR processors to detection of targets corresponding to Swerling model 1 against a normal noise background with unknown power associated with clutter and/or scattering from irregularities of the propagation medium.Key words: target detection, false alarm rate, detection threshold, signal-to-noise ratio, cell averagingManuscript submitted 26.06.2017Radio phys. radio astron. 2017, 22(3): 231-237REFERENCES1. LEVIN, B. R., 1968. Theoretical fundamentals of statistical radio engineering, Volume 2. Moscow, USSR: Sov. Radio Publ. (in Russian). 2. KAY, S. M., 1998. Fundamentals of Statistical Signal Processing, Vol. II: Detection Theory. New Jersey: Prentice Hall. 3. BARTON, D. K., 1998. Modern Radar System Analysis. Boston, London: Artech House Books. 4. SKOLNIK, M. I., 2008. Radar Handbook. New York et al.: McGraw Hill Professional. 5. BAKULEV, P. A., BASISTOV, Y. A. and TUGUSHI, V. G., 1989. Signal processing with a constant false alarm rate. Izv. Vyssh. Uchebn. Zaved. Radioelektronika. vol. 32, no. 4, pp. 4 15 (in Russian). 6. HAYKIN, S., 2007. Adaptive Radar Signal Processing. New Jersey: John Wiley & Sons Inc. 7. EL MASHADE, M. B., 2014. Performance enhancement of conventional CFAR processors in ideal and multitarget environments. Radioelectron. Commun. Syst. vol. 57, is. 7, pp. 287 305. DOI: https://doi.org/10.3103/S0735272714070012 8. LONG CAI, XIAOCHUAN MA, QI XU, BIN LI and SHIWEI REN, 2011. Performance Analysis of Some New CFAR Detectors under Clutter. Journal of Computers. vol. 6, no. 6, pp. 1278 1285. DOI: https://doi.org/10.4304/jcp.6.6.1278-1285 9. FINN, H. M. and JOHNSON, R. S., 1968. Adaptive detection mode with threshold control as a function of spatially sampled clutter level estimates. RCA Rev. vol. 29, no. 3, pp. 414 464. 10. SWERLING, P., 1960. Probability of detection for fluctuating targets. IRE Trans. Inf. Theory. vol. 6, is. 2, pp. 269 308. DOI: https://doi.org/10.1109/TIT.1960.1057561 11. SIDOROV, Y. V., FEDORYUK, M. V. and SHABUNIN, M. I., 1989. Lectures on the theory of functions of complex variable. Moscow, USSR: Nauka Publ. (in Russian).