Synthetic aperture radar target detection using a neural network with fractal dimension

Yu-Chang Tzeng; Kun-Shan Chen

doi:10.1117/1.2227019

1 July 2006 Synthetic aperture radar target detection using a neural network with fractal dimension

Yu-Chang Tzeng, Kun-Shan Chen

Author Affiliations +

Optical Engineering, Vol. 45, Issue 7, 077002 (July 2006). https://doi.org/10.1117/1.2227019

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.

©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Yu-Chang Tzeng and Kun-Shan Chen "Synthetic aperture radar target detection using a neural network with fractal dimension," Optical Engineering 45(7), 077002 (1 July 2006). https://doi.org/10.1117/1.2227019

Published: 1 July 2006

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