DOA Estimation and Beamforming Using Spatially Under-Sampled AVS Arrays

Conference Paper (2017)
Author(s)

K. Nambur Ramamohan (TU Delft - Electrical Engineering, Mathematics and Computer Science, Microflown Technologies)

M.A. Coutiño Minguez (TU Delft - Electrical Engineering, Mathematics and Computer Science)

S.P. Chepuri (TU Delft - Electrical Engineering, Mathematics and Computer Science)

D. Fernandez Comesana (Microflown Technologies)

G. Leus (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Signal Processing Systems
DOI related publication
https://doi.org/10.1109/CAMSAP.2017.8313203 Final published version
More Info
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Publication Year
2017
Language
English
Research Group
Signal Processing Systems
Pages (from-to)
1-5
ISBN (print)
978-1-5386-1252-1
ISBN (electronic)
978-1-5386-1251-4
Event
2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (2017-12-10 - 2017-12-13), Willemstad, Curaçao
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206

Abstract

In this paper, we show the advantages of spatially under-sampled acoustic vector sensor (AVS) arrays over conventional acoustic pressure sensor (APS) arrays for performing direction-of-arrival (DOA) estimation and interference cancellation. We provide insights into the theoretical performance of an under-sampled AVS array with respect to its DOA estimation performance using the Cramér-Rao lower bound (CRLB). We also show that the minimum variance distortionless response (MVDR) beamformer suppresses the grating lobes considerably as compared to the classical (or Bartlett) beamformer leading to unambiguous DOA estimates. Finally, through zero-forcing (ZF) and minimization of maximum side lobe beamformers, the advantages of an under-sampled AVS array for interference cancellation are presented.