Abstract
A minimum mean square error filter for pattern recognition problems with input scene noise that is spatially disjoint (or nonoverlapping) with the target is described. The filter is designed to locate the target by producing a delta function output at the target position. The filter minimizes the mean square of the difference between the desired output delta function and the filter output in response to a noisy input data. We show that the filter output has a well defined peak and small sidelobes in the presence of spatially disjoint target and scene noise.
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