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Detection of weak patterns in radar ocean RCS images is complicated by the fact that signals and noise are interactive rather than additive and the ambient noise background is non Gaussian or even strongly non Gaussian at low grazing angles. This paper addresses this difficult problem with the aid of two simplifying assumptions: (1) the signal modulation is weak, and (2) departure from Gaussianity is small. In situations where this departure is large, an approach is suggested for reducing this non Gaussianity. The relevant weak signal detection theory, based on the Likelihood ratio, is reviewed and adapted for use in the analysis. The approach to this problem, similar to that previously used for complex images, is facilitated by approximating the multivariate probability distributions as a composite integral involving underlying processes which are assumed to be Gaussian. This formulation, subject to the approximations in the analysis, permits derivation of an ideal detection statistic (which determines the form of optimum receiver) and a signal/noise ratio which characterizes detection performance in the weak signal limit. Implications for image processing are discussed and directions for future analysis are suggested

The detection of weak signal patterns in radar ocean intensity images