Abstract

Recently several approaches have been presented in which the shape of the correlation peak is used to distinguish between target and clutter. The well-known maximum average correlation height (MACH) filter was specifically designed to produce similar correlation planes for target variations present in the training set. Results are presented of a study of certain generalizations of the MACH filter intended to enhance the performance in clutter. It is shown that by taking into account the nonoverlapping character of the background noise and focusing the MACH correlation plane similarity requirement to the peak neighborhood, it is possible to simultaneously achieve a small variation in correlation peak shape and high peak-to-sidelobe ratios for cluttered images.

© 2000 Optical Society of America

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