Spatial correlation analysis using canonical correlation decomposition for sparse sonar array processing

Authors:
Yinghui Zhao;Mahmood R. Azimi-Sadjadi;Neil Wachowski;Nick Klausner
Affiliations:
Department of Electrical & Computer Engineering, Colorado State University, Fort Collins, CO;Department of Electrical & Computer Engineering, Colorado State University, Fort Collins, CO;Department of Electrical & Computer Engineering, Colorado State University, Fort Collins, CO;Department of Electrical & Computer Engineering, Colorado State University, Fort Collins, CO
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

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Abstract

This paper uses the canonical correlation decomposition (CCD) framework to investigate the spatial correlation of sources captured using two spatially separated sensor arrays. The relationship between the canonical correlations of the observed signals and the spatial correlation coefficients of the source signals are first derived, including an analysis of the changes seen in this relationship under certain noise level and array geometry assumptions. Additionally, simulation results are presented that demonstrate the effects of different noise levels and array geometries on the canonical correlations for the case of two uniform linear sparse arrays.