A Modified Matrix CFAR Detector based on Maximum Eigenvalue for Target Detection in the Sea Clutter

Riemannian distance based matrix constant false alarm rate (CFAR) detector under small number of pulses provides a novel mechanism for detecting radar targets against the background of sea clutter. However, the computational complexity of this detector is heavy. In this paper, using the maximum eigenvalue, we propose two blind algorithms for rank one signal. The proposed methods achieve high detection rates with low computational complexity in which the maximum eigenvalue is employed as the test statistic to modify the Riemannian method. Furthermore, the CFAR property is derived by the group invariant theory. The computational complexity is also analyzed and simulation results verify the effectiveness of the proposed detection methods.