DocumentCode :
1918891
Title :
Evaluation of partially adaptive STAP algorithms on the Mountain Top data set
Author :
Seliktar, Yaron ; Williams, Douglas B. ; McClellan, James H.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
2
fYear :
1996
fDate :
7-10 May 1996
Firstpage :
1169
Abstract :
In this paper we introduce a common framework for evaluating the performance of multiple weight, partially adaptive space-time adaptive processing (STAP) algorithms in terms of composite weight vectors. We then evaluate the performance of these STAP algorithms using synthetic and Mountain Top (MT) data (for airborne early warning radar) and address some limitations of high dimensional STAP algorithms in a nonstationary clutter environment. As part of the evaluation, we also familiarize the reader with the MT database and address important issues in processing the data
Keywords :
adaptive signal processing; airborne radar; military systems; radar clutter; radar signal processing; search radar; Mountain Top data set; airborne early warning radar; composite weight vectors; database; high dimensional STAP algorithms; nonstationary clutter environment; partially adaptive STAP algorithms; performance; space-time adaptive processing algorithms; Adaptive arrays; Array signal processing; Contracts; Covariance matrix; Data engineering; Data visualization; Frequency; Pattern analysis; Space technology; Visual databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1520-6149
Print_ISBN :
0-7803-3192-3
Type :
conf
DOI :
10.1109/ICASSP.1996.543573
Filename :
543573
Link To Document :
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