A CFAR thresholding approach based on test cell statistics

A new constant false alarm rate (CFAR) detection algorithm, that takes into account the statistics of the sample in the test cell for reference sample selection, is proposed and analysed. The new CFAR algorithm, designated as switching CFAR (S-CFAR), is designed to operate in a homogeneous environment and multiple targets with clutter transition situations. Mathematical analysis in an homogeneous environment shows that the S-CFAR processor has very small CFAR loss compared to the conventional cell-averaging CFAR processor. Monte-Carlo simulations in a non-homogeneous environment demonstrate that the S-CFAR processor has improved robustness against interference targets and clutter power transitions. The S-CFAR processor is also simple to design and implement, since no sample ordering is required.