Direction of arrival estimation based on support vector regression: Experimental validation and comparison with MUSIC

A. Randazzo; M. A. Abou-Khousa; M. Pastorino; R. Zoughi

doi:10.1109/LAWP.2007.903491

Direction of arrival estimation based on support vector regression: Experimental validation and comparison with MUSIC

A. Randazzo, M. A. Abou-Khousa, M. Pastorino, R. Zoughi

Electrical Engineering

Research output: Contribution to journal › Article › peer-review

93 Scopus citations

Abstract

In this letter, the problem of estimating the directions of arrival (DOAs) of coherent electromagnetic waves impinging upon a uniform linear array (ULA) is considered. In particular, an efficient DOA estimation approach based on the support vector regression is assessed using experimental measurements. Moreover, the obtained results are compared with those yielded by the multiple signal classification (MUSIC) algorithm.

Original language	British English
Article number	903491
Pages (from-to)	379-382
Number of pages	4
Journal	IEEE Antennas and Wireless Propagation Letters
Volume	6
DOIs	https://doi.org/10.1109/LAWP.2007.903491
State	Published - 2007

Keywords

Directions of arrival (doas)
Support vector machines (svms)/regression
Uniform linear array (ula)

Access to Document

10.1109/LAWP.2007.903491

Cite this

@article{b58850efcdc14bf59b267254df297d3c,

title = "Direction of arrival estimation based on support vector regression: Experimental validation and comparison with MUSIC",

abstract = "In this letter, the problem of estimating the directions of arrival (DOAs) of coherent electromagnetic waves impinging upon a uniform linear array (ULA) is considered. In particular, an efficient DOA estimation approach based on the support vector regression is assessed using experimental measurements. Moreover, the obtained results are compared with those yielded by the multiple signal classification (MUSIC) algorithm.",

keywords = "Directions of arrival (doas), Support vector machines (svms)/regression, Uniform linear array (ula)",

author = "A. Randazzo and Abou-Khousa, {M. A.} and M. Pastorino and R. Zoughi",

year = "2007",

doi = "10.1109/LAWP.2007.903491",

language = "British English",

volume = "6",

pages = "379--382",

journal = "IEEE Antennas and Wireless Propagation Letters",

issn = "1536-1225",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Direction of arrival estimation based on support vector regression

T2 - Experimental validation and comparison with MUSIC

AU - Randazzo, A.

AU - Abou-Khousa, M. A.

AU - Pastorino, M.

AU - Zoughi, R.

PY - 2007

Y1 - 2007

N2 - In this letter, the problem of estimating the directions of arrival (DOAs) of coherent electromagnetic waves impinging upon a uniform linear array (ULA) is considered. In particular, an efficient DOA estimation approach based on the support vector regression is assessed using experimental measurements. Moreover, the obtained results are compared with those yielded by the multiple signal classification (MUSIC) algorithm.

AB - In this letter, the problem of estimating the directions of arrival (DOAs) of coherent electromagnetic waves impinging upon a uniform linear array (ULA) is considered. In particular, an efficient DOA estimation approach based on the support vector regression is assessed using experimental measurements. Moreover, the obtained results are compared with those yielded by the multiple signal classification (MUSIC) algorithm.

KW - Directions of arrival (doas)

KW - Support vector machines (svms)/regression

KW - Uniform linear array (ula)

UR - http://www.scopus.com/inward/record.url?scp=68949202035&partnerID=8YFLogxK

U2 - 10.1109/LAWP.2007.903491

DO - 10.1109/LAWP.2007.903491

M3 - Article

AN - SCOPUS:68949202035

SN - 1536-1225

VL - 6

SP - 379

EP - 382

JO - IEEE Antennas and Wireless Propagation Letters

JF - IEEE Antennas and Wireless Propagation Letters

M1 - 903491

ER -

Direction of arrival estimation based on support vector regression: Experimental validation and comparison with MUSIC

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this