Aircraft target recognition using adaptive time-delay neural network

Author

Xiao Huaitie ; Zhuang Zhaowen ; Chen Zhenpin ; Songhua, He ; Guo Biao

Author_Institution

Nat. Univ. of Defense Technol., Hunan, China

Volume

2

fYear

1997

fDate

14-18 Jul 1997

Firstpage

764

Abstract

In this paper, an adaptive time-delay neural network (ATDNN) classifier based on high resolution radar down range profiles is proposed for use in aircraft target recognition, and a peak-based feature extraction technique for the range profiles is introduced. The results of experiments show that the average correct recognition rate of scale model aircrafts is 87.6% under the condition of three kinds of aircrafts

Keywords

adaptive signal processing; backpropagation; feature extraction; multilayer perceptrons; pattern classification; radar computing; radar cross-sections; radar signal processing; radar target recognition; radar tracking; target tracking; time series; adaptive time-delay neural network; aircraft target recognition; average correct recognition rate; delay blocks; error backpropagation; gradient descent method; high resolution radar down range profiles; multilayered network; peak-based feature extraction technique; radar backscatter signals; range profiles; scale model aircrafts; thresholding; total RCS; Adaptive systems; Aircraft; Neural networks; Pattern recognition; Radar cross section; Radar measurements; Radar scattering; Signal processing; Signal resolution; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Aerospace and Electronics Conference, 1997. NAECON 1997., Proceedings of the IEEE 1997 National

Conference_Location

Dayton, OH

Print_ISBN

0-7803-3725-5

Type

conf

DOI

10.1109/NAECON.1997.622726

Filename

622726