Durbin test with enhanced detection performance to mismatched signal

This paper deals with the problem of detecting a signal known up to a scaling factor in the presence of homogeneous Gaussian noise with unknown covariance matrix. Since no uniformly most powerful test exists for the problem at hand, we devise and assess a detection strategy based on the well-known Durbin test design criteria. The closed-form expressions for the probabilities of false alarm and detection of the Durbin test are derived, which show that it bears a constant false alarm rate property against the noise covariance matrix. At the analysis stage, the performance of the new receiver is assessed, also in comparison with some classical adaptive detectors, both in the matched and in the mismatched signal case. The results show that the proposed detector achieves a visible performance improvement in the presence of severe steering vector mismatch, while maintaining an acceptable detection loss for matched signal. Adaptive detection, Homogeneous scenario, Durbin test, Constant false alarm rate.