Analytical and Experimental Results for Maximizing the Pull-in Range of Product Correlators

Product correlators are being developed and implemented as a means of improving the guidance capability of tactical missiles. Analytical and experimental results are presented for maximizing the pull-in range of product area correlators via investigation of the discriminator curve of the correlator. The maps used in the correlation are assumed to be sample functions from two-dimensional, zero-mean, stationary Gaussian random processes. To obtain closed-form results, the additional assumption of a Gaussian correlation function is made. These analyses and results should be applicable to a wide range of correlation systems. Implications of these results as they pertain to missile guidance are discussed.