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

DOI: https://doi.org/10.15407/rpra22.03.231

V. G. Galushko

Abstract


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

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Keywords


target detection; false alarm rate; detection threshold; signal-to-noise ratio; cell averaging

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