An adaptive detector for detecting target in clutter plus Gaussian noise background

In this paper, the problem of target detection in the clutter plus Gaussian noise background is considered. The published detectors group the clutter and the noise as a single parameter; differently, we deal separately with the clutter and the noise. In the paper, the noise is assumed to be obtained in advance and the clutter is distributed according to a certain distribution. An adaptive target detector which utilizes the maximum likelihood estimate (MLE) of the clutter covariance and the MLE of the signal of interest (SOI) is proposed. The detector has a simpler expression than the published detectors. To validate its detection performance, the proposed detector is compared with three published detectors. Numerical experimental results demonstrate that the proposed detector has better detection performance; moreover, the proposed detector can obtain reliable detection performance with less secondary data.