DocumentCode :
1335510
Title :
Aircraft identification from RCS measurement using an orthogonal transform
Author :
Chan, Y.T. ; Ho, K.C. ; Wong, S.K.
Author_Institution :
Dept. of Electr. & Comput. Eng., R. Mil. Coll. of Canada, Kingston, Ont., Canada
Volume :
147
Issue :
2
fYear :
2000
fDate :
4/1/2000 12:00:00 AM
Firstpage :
93
Lastpage :
102
Abstract :
A comparative study on target identification using the radar cross section (RCS) signature of an aircraft in both the frequency domain and the range domain is conducted. A maximum likelihood method is employed to perform the identification process. Generalised likelihood identification when the received RCS signal is attenuated by an unknown amount is also examined. Target identification could be quite computationally intensive since a large number of library reference signatures may have to be searched to declare an identification. The use of an orthogonal transform is proposed to reduce the computational requirement. It is found that the discrete cosine transform is very effective in compacting the RCS signature in the frequency domain, and the Haar transform is more efficient in the range domain. The application of orthogonal transforms can reduce the computational complexity by at least 50% while maintaining the same identification accuracy
Keywords :
Haar transforms; aircraft; computational complexity; discrete cosine transforms; frequency-domain analysis; maximum likelihood estimation; radar applications; radar cross-sections; radar target recognition; Haar transform; RCS measurement; RCS signature; aircraft identification; computational complexity reduction; discrete cosine transform; frequency domain; generalised likelihood identification; identification accuracy; library reference signatures; maximum likelihood method; orthogonal transform; radar cross section signature; range domain; received RCS signal attenuation; target identification;
fLanguage :
English
Journal_Title :
Radar, Sonar and Navigation, IEE Proceedings -
Publisher :
iet
ISSN :
1350-2395
Type :
jour
DOI :
10.1049/ip-rsn:20000240
Filename :
842163
Link To Document :
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