Structures for radar detection in compound Gaussian clutter

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.