Joint estimation of direction of departure and direction of arrival for multiple-input multiple-output radar based on improved joint ESPRIT method

Daegun Oh; Ying Chun Li; Jasurbek Khodjaev; Jong Wha Chong; Jong Hun Lee

doi:10.1049/iet-rsn.2014.0069

Joint estimation of direction of departure and direction of arrival for multiple-input multiple-output radar based on improved joint ESPRIT method

Daegun Oh, Ying Chun Li, Jasurbek Khodjaev, Jong Wha Chong, Jong Hun Lee

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35 Scopus citations

Abstract

This study presents an improved joint estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm for low-complexity simultaneous estimation of direction of departure (DOD) and direction of arrival (DOA) in a multiple-input-multiple-output radar system. The proposed algorithm is based on a data matrix and estimates DOD and DOA without a pairing operation. The computational complexity of the proposed joint ESPRIT algorithm is derived to be less than that of conventional two dimension multiple signal classification (2D-MUSIC) and reduced dimension multiple signal classification. The authors' simulation results demonstrate that the proposed algorithm achieves performance very close to that of 2D-MUSIC and better performance than that of the ESPRIT algorithm.

Original language	English
Pages (from-to)	308-317
Number of pages	10
Journal	IET Radar, Sonar and Navigation
Volume	9
Issue number	3
DOIs	https://doi.org/10.1049/iet-rsn.2014.0069
State	Published - 1 Mar 2015

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© The Institution of Engineering and Technology 2015.

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title = "Joint estimation of direction of departure and direction of arrival for multiple-input multiple-output radar based on improved joint ESPRIT method",

abstract = "This study presents an improved joint estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm for low-complexity simultaneous estimation of direction of departure (DOD) and direction of arrival (DOA) in a multiple-input-multiple-output radar system. The proposed algorithm is based on a data matrix and estimates DOD and DOA without a pairing operation. The computational complexity of the proposed joint ESPRIT algorithm is derived to be less than that of conventional two dimension multiple signal classification (2D-MUSIC) and reduced dimension multiple signal classification. The authors' simulation results demonstrate that the proposed algorithm achieves performance very close to that of 2D-MUSIC and better performance than that of the ESPRIT algorithm.",

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T1 - Joint estimation of direction of departure and direction of arrival for multiple-input multiple-output radar based on improved joint ESPRIT method

AU - Oh, Daegun

AU - Li, Ying Chun

AU - Khodjaev, Jasurbek

AU - Chong, Jong Wha

AU - Lee, Jong Hun

PY - 2015/3/1

Y1 - 2015/3/1

N2 - This study presents an improved joint estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm for low-complexity simultaneous estimation of direction of departure (DOD) and direction of arrival (DOA) in a multiple-input-multiple-output radar system. The proposed algorithm is based on a data matrix and estimates DOD and DOA without a pairing operation. The computational complexity of the proposed joint ESPRIT algorithm is derived to be less than that of conventional two dimension multiple signal classification (2D-MUSIC) and reduced dimension multiple signal classification. The authors' simulation results demonstrate that the proposed algorithm achieves performance very close to that of 2D-MUSIC and better performance than that of the ESPRIT algorithm.

AB - This study presents an improved joint estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm for low-complexity simultaneous estimation of direction of departure (DOD) and direction of arrival (DOA) in a multiple-input-multiple-output radar system. The proposed algorithm is based on a data matrix and estimates DOD and DOA without a pairing operation. The computational complexity of the proposed joint ESPRIT algorithm is derived to be less than that of conventional two dimension multiple signal classification (2D-MUSIC) and reduced dimension multiple signal classification. The authors' simulation results demonstrate that the proposed algorithm achieves performance very close to that of 2D-MUSIC and better performance than that of the ESPRIT algorithm.

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Joint estimation of direction of departure and direction of arrival for multiple-input multiple-output radar based on improved joint ESPRIT method

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