DOA estimation and beamforming using spatially under-sampled AVS arrays

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

doi:10.1109/CAMSAP.2017.8313203

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 proceeding › Conference contribution

4 Scopus citations

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.

Original language	English (US)
Title of host publication	2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Publisher	IEEE
Pages	1-5
Number of pages	5
ISBN (Print)	9781538612514
DOIs	https://doi.org/10.1109/CAMSAP.2017.8313203
State	Published - Mar 12 2018
Externally published	Yes

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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10.1109/CAMSAP.2017.8313203

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@inproceedings{82cbc105db4a46d89942f2734dd8b9c2,

title = "DOA estimation and beamforming using spatially under-sampled AVS arrays",

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 Cram{\'e}r-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.",

author = "Krishnaprasad, {N. R.} and Mario Contino and Chepuri, {Sundeep Prabhakar} and Comesa{\~n}a, {Daniel Fern{\'a}ndez} and Geert Leus",

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.",

year = "2018",

month = mar,

day = "12",

doi = "10.1109/CAMSAP.2017.8313203",

language = "English (US)",

isbn = "9781538612514",

pages = "1--5",

booktitle = "2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)",

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T1 - DOA estimation and beamforming using spatially under-sampled AVS arrays

AU - Krishnaprasad, N. R.

AU - Contino, Mario

AU - Chepuri, Sundeep Prabhakar

AU - Comesaña, Daniel Fernández

AU - Leus, Geert

N1 - 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.

PY - 2018/3/12

Y1 - 2018/3/12

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10754/679442

UR - http://ieeexplore.ieee.org/document/8313203/

UR - http://www.scopus.com/inward/record.url?scp=85051126812&partnerID=8YFLogxK

U2 - 10.1109/CAMSAP.2017.8313203

DO - 10.1109/CAMSAP.2017.8313203

M3 - Conference contribution

SN - 9781538612514

SP - 1

EP - 5

BT - 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

PB - IEEE

ER -

DOA estimation and beamforming using spatially under-sampled AVS arrays

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