Abstract
The fractal dimension is used in conjunction with a neural network to quantify effects of the chaotic behavior of radar clutter on the geometric aspects of target detection by synthetic aperture radar. To demonstrate the effectiveness of the proposed method, results are compared with those of the conventional constant-false-alarm-rate algorithm and the neural network technique. It is shown that the use of the fractal dimension substantially improves the detection performance based on some figures of merit, including detection rate, false-detection rate, and loss detection rate.
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