An Augmented Generalized Likelihood Ratio Test Detector for Signal Detection in Clutter and Noise

To deal with the problem of signal detection in correlated subspace, this paper presents an augmented generalized likelihood ratio test (AGLRT) detector. Compared with traditional GLRT detector, this AGLRT detector has the advantage of incorporating the intersection component between signal and clutter subspace. Signal-contribution-ratio (SCR) and clutter-contribution-ratio (CCR) are defined to characterize the contribution of signal and clutter in the common subspace, respectively. The closed forms of both probability of detection and false alarm for the AGLRT detector are presented. It is shown that the detection performance of the AGLRT detector is better than the GLRT detector by choosing appropriate weight and threshold parameters. Then, analytical formulas of the suboptimal weight and threshold to maximize the detection performance are obtained. Finally, the effectiveness of the proposed detector is demonstrated by various examples.