DOA estimation and beamforming using spatially under-sampled AVS arrays

N. R. Krishnaprasad, Mario Contino, Sundeep Prabhakar Chepuri, Daniel Fernández Comesaña, Geert Leus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


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.
Original languageEnglish (US)
Title of host publication2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Number of pages5
ISBN (Print)9781538612514
StatePublished - Mar 12 2018
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-30
Acknowledged KAUST grant number(s): OSR-2015-Sensors-2700
Acknowledgements: This work is supported in part by the ASPIRE project (project 14926 within the STW OTP programme), which is financed by the Netherlands Organization for Scientific Research (NWO) and the KAUST-MIT-TUD consortium under grant OSR-2015-Sensors-2700. Mario Coutino is partially supported by CONACYT.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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