سال انتشار: ۱۳۸۲

محل انتشار: یازدهمین کنفرانس مهندسی برق

تعداد صفحات: ۸

نویسنده(ها):

Ali Kabiri – Department of Physics, Tehran University, Tehran, Iran
Nima Sarshar – Electrical Engineering Department, McMaster University, Canada
Kasra Barkeshli – Electrical Engineering Department, Sharif University of Technology, Tehran, Iran

چکیده:

A new method for the robust estimation of target orientation using measured echo-width data will be pproposed in this paper. The method is based on a Generalized Regression Neural Network (GRNN) scheme. GRNN belongs to the family of radial basis neural networks. It is a memory based network which provides estimates of continuous variables and converges to the underlying optimal linear or nonlinear regression surface. The network is trained by the FFT modulus of bistatic radar cross section data sampled at the receiver positions. Noisy data, produced by displacing the receivers, were added to the training data set to enhance the robustness of the method.