The problem of coherent radar target detection in a background of non-Gauss
ian clutter modeled by a compound Gaussian distribution is studied here. We
show how the likelihood ratio may be recast into an estimator-correlator f
orm that shows that an essential feature of the optimal detector is to comp
ute an optimum estimate of the reciprocal of the unknown random local power
level. We then proceed to show that the optimal detector may be recast int
o yet another form, namely a matched filter compared with a data-dependent
threshold. With these reformulations of the optimal detector, the problem o
f obtaining suboptimal detectors may be systematically studied by either ap
proximating the likelihood ratio directly, utilizing a suboptimal estimate
in the estimator-correlator structure or utilizing a suboptimal function to
model the data-dependent threshold in the matched biter interpretation. Ea
ch of these approaches is studied to obtain suboptimal detectors. The resul
ts indicate that for processing small numbers of pulses, a suboptimal detec
tor that utilizes information about the nature of the non-Gaussian clutter
can be implemented to obtain quasi-optimal performance. As the number of pu
lses to be processed increases, a suboptimal detector that does not require
information about the specific nature of the non-Gaussian clutter may be i
mplemented to obtain quasi-optimal performance.