A comparison of the eigenvector weighting and Gram-Schmidt adaptive antenna techniques

Eigenvector and Gram-Schmidt weighting separate desired signals from interference without a priori information. For two signals and similar element patterns, eigenvector performance varies between Gram-Schmidt power inversion and perfect signal separation, depending on signal direction and array geo...

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Bibliographic Details
Published inIEEE transactions on aerospace and electronic systems Vol. 29; no. 2; pp. 568 - 575
Main Authors Jenkins, R.W., Moreland, K.W.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.04.1993
Institute of Electrical and Electronics Engineers
Subjects
Adaptive arrays
Applied sciences
Constraint optimization
Exact sciences and technology
Information, signal and communications theory
Interference
Lagrangian functions
Military computing
Minimization methods
Sensor fusion
Source separation
Systems engineering and theory
Target tracking
Telecommunications and information theory
Adaptive antenna
Weighting
Eigenvector
Signal estimation
Interference
Performance
Algorithm
Modeling
Signal detection
Comparative study
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Summary:Eigenvector and Gram-Schmidt weighting separate desired signals from interference without a priori information. For two signals and similar element patterns, eigenvector performance varies between Gram-Schmidt power inversion and perfect signal separation, depending on signal direction and array geometry. For nearly equal input powers, Gram-Schmidt always fails but eigenvector weighting often succeeds.< >
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0018-9251
1557-9603
DOI:10.1109/7.210095