Fast detection and location of failed array elements using the fast SVM algorithm

With the increased proliferation of array antennas, for a myriad of wireless applications, the monitoring and correction of array element failure is becoming more critical. In this paper, a fast Support Vector Machine (SVM) classifier, based on low-degree polynomial kernel is developed, to expeditio...

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Bibliographic Details
Published in2010 14th International Symposium on Antenna Technology and Applied Electromagnetics & the American Electromagnetics Conference pp. 1 - 4
Main Authors Beng-Kiong Yeo, Yilong Lu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2010
Subjects
analog beam forming
antenna arrays
Array failure detection
Arrays
Artificial neural networks
Binary codes
Kernel
Polynomials
support vector machine
Support vector machines
Training
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Summary:With the increased proliferation of array antennas, for a myriad of wireless applications, the monitoring and correction of array element failure is becoming more critical. In this paper, a fast Support Vector Machine (SVM) classifier, based on low-degree polynomial kernel is developed, to expeditiously detect and locate the failed elements of an arbitrary analog array, while categorizing the level of failure, at the same time. This method will work on any analog array configuration, and the results for a linear array sample are illustrated to demonstrate its effectiveness.
ISBN:1424450497
9781424450497
DOI:10.1109/ANTEM.2010.5552576