DocumentCode :
298125
Title :
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
Link To Document :
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