Evaluating Correlation Between Measurement Samples in Reverberation Chambers Using Clustering

Traditionally, in reverberation chambers (RC) measurement autocorrelation or correlation-matrix methods have been applied to evaluate measurement correlation. In this article, we introduce the use of clustering based on correlative distance to group correlated measurements. We apply the method to me...

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Bibliographic Details
Published in2023 101st ARFTG Microwave Measurement Conference (ARFTG) pp. 01 - 05
Main Authors Nogueira, Carnot L., Remley, Kate A., Jones, Robert D., Horansky, Robert D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 16.06.2023
Subjects
Adjacency matrix
Autocorrelation
clustering analysis
correlation
Correlation coefficient
correlative distance
Electromagnetic fields
Extraterrestrial measurements
Microwave measurement
mode-stirring samples
Pearson correlation coefficient (PCC)
Position measurement
Reverberation chambers
reverberation chambers (RC)
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Summary:Traditionally, in reverberation chambers (RC) measurement autocorrelation or correlation-matrix methods have been applied to evaluate measurement correlation. In this article, we introduce the use of clustering based on correlative distance to group correlated measurements. We apply the method to measurements taken in an RC using one and two paddles to stir the electromagnetic fields and applying decreasing angular steps between consecutive paddles' positions. The results - using varying correlation threshold values - demonstrate that the method calculates the number of effective samples and allows discerning outliers, i.e., uncorrelated measurements, and clusters of correlated measurements. This calculation method allows for non-sequential stir sequence design which can reduce testing time.
ISSN:2767-8776
DOI:10.1109/ARFTG57476.2023.10278668