Automatic censored mean level detector using a variability-based censoring with non-coherent integration

Authors:
Atef Farrouki;Mourad Barkat
Affiliations:
Département d'Electronique, Université de Constantine, Route de Ain El Bey, Constantine 25000, Algeria;Department of Electrical Engineering, American University of Sharjah, P.O. Box 26666, Sharjah, UAE
Venue:
Signal Processing
Year:
2007

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Abstract

Radar detection is impaired by the presence of clutter transitions or interfering targets within the reference channel. In this paper, we propose an automatic censoring constant false alarm rate (CFAR) detector processing for multiple target situations and using multiple non-coherent pulse integration. The proposed detection scheme is based on an optimal selection of the appropriate censored mean level according to the actual background environment and thus, we call it Opt-CMLD. In particular, we use an automatic data variability-based censoring technique to generate a suitable ranked subset for the background level estimate, and derive an exact expression for the probability of false alarm, Pfa. Then, the performance analysis of the proposed Opt-CMLD is studied for M non-coherent integrated pulses in both a homogeneous environment and multiple target situations.