Adaptive measurement matrix design for compressed DoA estimation with sensor arrays

Berk Ozer; Anastasia Lavrenko; Sinan Gezici; Florian Romer; Giovanni Del Galdo; Orhan Arikan

doi:10.1109/ACSSC.2015.7421455

Adaptive measurement matrix design for compressed DoA estimation with sensor arrays

Berk Ozer^*
, Anastasia Lavrenko
, Sinan Gezici
, Florian Romer
, Giovanni Del Galdo
, Orhan Arikan

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

Abstract

In this work we consider the problem of measurement matrix design for compressed 3-D Direction of Arrival (DoA) estimation using a sensor array with analog combiner. Since generic measurement matrix designs often do not yield optimal estimation performance, we propose a novel design technique based on the minimization of the Cramér-Rao Lower Bound (CRLB). We develop specific approaches for adaptive measurement design for two applications: detection of the newly appearing targets and tracking of the previously detected targets. Numerical results suggest that the developed designs allow to provide the near optimal performance in terms of the CRLB.

Original language	English
Title of host publication	Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Editors	Michael B. Matthews
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	1769-1773
Number of pages	5
ISBN (Electronic)	978-1-4673-8576-3, 978-1-4673-8574-9 (CD), 978-1-4673-8575-6 (USB)
DOIs	https://doi.org/10.1109/ACSSC.2015.7421455
Publication status	Published - 26 Feb 2016
Externally published	Yes
Event	49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States Duration: 8 Nov 2015 → 11 Nov 2015 Conference number: 49

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Publisher	IEEE
Number	49
Volume	2016
ISSN (Print)	1058-6393

Conference

Conference	49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Abbreviated title	ACSSC 2015
Country/Territory	United States
City	Pacific Grove
Period	8/11/15 → 11/11/15

Keywords

n/a OA procedure

Access to Document

10.1109/ACSSC.2015.7421455

Cite this

Ozer, B., Lavrenko, A., Gezici, S., Romer, F., Galdo, G. D., & Arikan, O. (2016). Adaptive measurement matrix design for compressed DoA estimation with sensor arrays. In M. B. Matthews (Ed.), Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 (pp. 1769-1773). Article 7421455 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2016, No. 49). IEEE. https://doi.org/10.1109/ACSSC.2015.7421455

Ozer, Berk ; Lavrenko, Anastasia ; Gezici, Sinan et al. / Adaptive measurement matrix design for compressed DoA estimation with sensor arrays. Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015. editor / Michael B. Matthews. Piscataway, NJ : IEEE, 2016. pp. 1769-1773 (Conference Record - Asilomar Conference on Signals, Systems and Computers; 49).

@inproceedings{d6379ba15e3c4fa3b9ae505e60712900,

title = "Adaptive measurement matrix design for compressed DoA estimation with sensor arrays",

abstract = "In this work we consider the problem of measurement matrix design for compressed 3-D Direction of Arrival (DoA) estimation using a sensor array with analog combiner. Since generic measurement matrix designs often do not yield optimal estimation performance, we propose a novel design technique based on the minimization of the Cram{\'e}r-Rao Lower Bound (CRLB). We develop specific approaches for adaptive measurement design for two applications: detection of the newly appearing targets and tracking of the previously detected targets. Numerical results suggest that the developed designs allow to provide the near optimal performance in terms of the CRLB.",

keywords = "n/a OA procedure",

author = "Berk Ozer and Anastasia Lavrenko and Sinan Gezici and Florian Romer and Galdo, \{Giovanni Del\} and Orhan Arikan",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015, ACSSC 2015 ; Conference date: 08-11-2015 Through 11-11-2015",

year = "2016",

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doi = "10.1109/ACSSC.2015.7421455",

language = "English",

series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

publisher = "IEEE",

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booktitle = "Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015",

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Ozer, B, Lavrenko, A, Gezici, S, Romer, F, Galdo, GD & Arikan, O 2016, Adaptive measurement matrix design for compressed DoA estimation with sensor arrays. in MB Matthews (ed.), Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015., 7421455, Conference Record - Asilomar Conference on Signals, Systems and Computers, no. 49, vol. 2016, IEEE, Piscataway, NJ, pp. 1769-1773, 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015, Pacific Grove, California, United States, 8/11/15. https://doi.org/10.1109/ACSSC.2015.7421455

Adaptive measurement matrix design for compressed DoA estimation with sensor arrays. / Ozer, Berk; Lavrenko, Anastasia; Gezici, Sinan et al.
Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015. ed. / Michael B. Matthews. Piscataway, NJ: IEEE, 2016. p. 1769-1773 7421455 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2016, No. 49).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Adaptive measurement matrix design for compressed DoA estimation with sensor arrays

AU - Ozer, Berk

AU - Lavrenko, Anastasia

AU - Gezici, Sinan

AU - Romer, Florian

AU - Galdo, Giovanni Del

AU - Arikan, Orhan

N1 - Conference code: 49

PY - 2016/2/26

Y1 - 2016/2/26

N2 - In this work we consider the problem of measurement matrix design for compressed 3-D Direction of Arrival (DoA) estimation using a sensor array with analog combiner. Since generic measurement matrix designs often do not yield optimal estimation performance, we propose a novel design technique based on the minimization of the Cramér-Rao Lower Bound (CRLB). We develop specific approaches for adaptive measurement design for two applications: detection of the newly appearing targets and tracking of the previously detected targets. Numerical results suggest that the developed designs allow to provide the near optimal performance in terms of the CRLB.

AB - In this work we consider the problem of measurement matrix design for compressed 3-D Direction of Arrival (DoA) estimation using a sensor array with analog combiner. Since generic measurement matrix designs often do not yield optimal estimation performance, we propose a novel design technique based on the minimization of the Cramér-Rao Lower Bound (CRLB). We develop specific approaches for adaptive measurement design for two applications: detection of the newly appearing targets and tracking of the previously detected targets. Numerical results suggest that the developed designs allow to provide the near optimal performance in terms of the CRLB.

KW - n/a OA procedure

UR - https://www.scopus.com/pages/publications/84969793645

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DO - 10.1109/ACSSC.2015.7421455

M3 - Conference contribution

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BT - Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015

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PB - IEEE

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T2 - 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015

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Ozer B, Lavrenko A, Gezici S, Romer F, Galdo GD, Arikan O. Adaptive measurement matrix design for compressed DoA estimation with sensor arrays. In Matthews MB, editor, Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015. Piscataway, NJ: IEEE. 2016. p. 1769-1773. 7421455. (Conference Record - Asilomar Conference on Signals, Systems and Computers; 49). doi: 10.1109/ACSSC.2015.7421455

Adaptive measurement matrix design for compressed DoA estimation with sensor arrays

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