A range-coherent model for discriminating targets and wave clutter in high range resolution surface radar

A statistical model for the complex data of high range resolution surface radars is proposed that incorporates range coherence in both the clutter and target. The clutter is modeled using two distributions: a background clutter distribution and wave clutter distribution. The model is then used to develop a multi-hypothesis detector that discriminates between targets, wave clutter, and background clutter. Performance on real surface radar data shows that this technique reduces false alarms due to wave clutter spikes more effectively than the cell-averaging constant false alarm rate (CA-CFAR) detector that operates on the amplitude data using a composite clutter model.