Approach to reach high range resolution by using neural networks

Author

Zhang, Wenfeng ; He, Songhua ; Guo, Guirong

Author_Institution

ATR Lab., Nat. Univ. of Defense Tech., Hunan, China

Volume

1

fYear

1996

fDate

20-23 May 1996

Firstpage

188

Abstract

For automatic target recognition, especially on high resolution radars, range profiles are very important, because they can be used to describe the accurate geometric shape and structural features of targets, and can be obtained in a few periods of pulse, and then, the real-time data processing realized easily. However, the traditional algorithms can not give us satisfactory resolution. In this paper, neural networks are used to reach high range resolution, and recognize these range profiles

Keywords

Hopfield neural nets; fast Fourier transforms; learning (artificial intelligence); military computing; radar target recognition; telecommunication computing; FFT; Hopfield linear programming neural net; Tank neural net; automatic target recognition; geometric shape; high range resolution; military targets; neural networks; radar target recognition; range profiles; real-time data processing; structural features; Artificial neural networks; Data processing; Helium; Linear programming; Neural networks; Parallel processing; Pulse shaping methods; Radar; Shape; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Aerospace and Electronics Conference, 1996. NAECON 1996., Proceedings of the IEEE 1996 National

Conference_Location

Dayton, OH

ISSN

0547-3578

Print_ISBN

0-7803-3306-3

Type

conf

DOI

10.1109/NAECON.1996.517638

Filename

517638