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Effects of correlation and seabed between multiple looks on the expected probability of detection of an underwater target

In this paper, we model an essential feature of underwater mine hunting with the aim of suggesting improvements to existing search tactics. We derive the effect of correlation between multiple sonar images of an underwater mine target - where a correlator represents the relation between images of the same target. For example, with duplicate images of the same target the correlator shows the absence of any additional information gain. However, when a contrasting image of a target is added to those already analyzed, the correlator proves the additional information gain. Our findings show that if correlation is weak, a specific set of equidistant angles will globally maximize the expected probability of detection.