A simplified parametric GLRT for STAP detection

We consider multichannel signal detection in the presence of spatially and temporally colored disturbance, a problem also known as space-time adaptive processing (STAP) in radars. A number of sample covariance matrix based STAP detectors have been proposed, which often require a lot of training data to ensure convergence. In many practical scenarios, these detectors may suffer significant performance loss due to a lack of sufficient training data. This has motivated interest in techniques with reduced training requirements, such as partially reduced rank-dimension detection, parametric STAP, and others.