Detection problem in mixed clutter environment as a Gaussian problem by adaptive preprocessing

The authors introduce an adaptive suboptimum procedure for the detection of a signal of known form in the presence of a disturbance, which is assumed to be a mixture of coherent K-distributed and Gaussian distributed clutter sources with unknown distributions. A generalised likelihood test is derived exploiting a simple idea: by normalising the clutter samples from each range cell with the estimated local power, the detection problem is reduced to a Gaussian problem and a simple adaptive detector is obtained