Application of point enhancement technique for ship target recognition by HRR

We present an evaluation of the impact of a recently developed point-enhanced high range-resolution (HRR) radar profile reconstruction method on automatic target recognition (ATR) performance. We use several pattern recognition techniques to compare the performance of point-enhanced HRR profiles with conventional Fourier transform-based profiles. We use measured radar data of civilian ships and produce range profiles from such data. We use two types of classifiers to quantify recognition performance. The first type of classifier is based on the nearest neighbor technique. We demonstrate the performance of this classifier using a variety of extracted features, and a number of different distance metrics. The second classifier we use for target recognition involves position specific matrices, which have previously been used in gene sequencing. We compare the classification performance of point-enhanced HRR profiles with conventional profiles, and observe that point enhancement results in higher recognition rates in general.

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