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 averaging Manuscript submitted 26.06.2017 Radio phys. radio astron. 2017, 22(3): 231-237 REFERENCES 1. 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).
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