CFAR Detection from Noncoherent Radar Echoes Using Bayesian Theory

Abstract

We propose a new constant false alarm rate (CFAR) detection method from noncoherent radar echoes, considering heterogeneous sea clutter. It applies the Bayesian theory for adaptive estimation of the local clutter statistical distribution in the cell under test. The detection technique can be readily implemented in existing noncoherent marine radar systems, which makes it particularly attractive for economical CFAR detection systems. Monte Carlo simulations were used to investigate the detection performance and demonstrated that the proposed technique provides a higher probability of detection than conventional techniques, such as cell averaging CFAR (CA-CFAR), especially with a small number of reference cells.

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