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Real-time polarization-diverse features extraction and automated target identification using neural networks

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2 Author(s)
Liang-jie Zhang ; Dept. of Inf. & Control Eng., Xi'an Jiao-Tong Univ., Shaanxi, China ; Wen-bing Wang

The authors have mapped the polarization-diverse features extraction problem onto the Lyapunov energy function of the Hopfield model neural network to obtain the real-time solution of the feature, i.e., the ellipticity, the tilt angle and the amplitude of the fit ellipse, derived from this parameterization. Simulated results are presented to shows its real-time capacity in the context of the polarization-diverse features extraction problem by using the Hopfield net as well as its strong target identification ability by applying the back-propagation neural network employing the resulting feature sets. The approaches considered here are expected to have a faster computational speed than those of the traditional approaches such as the LMS (least mean square) approximation method and classical pattern recognition.<>

Published in:

Antennas and Propagation Society International Symposium, 1992. AP-S. 1992 Digest. Held in Conjuction with: URSI Radio Science Meeting and Nuclear EMP Meeting., IEEE

Date of Conference:

18-25 June 1992