Joint DOD and DOA Estimation for NLOS Target Using IRS-Aided Bistatic MIMO Radar

Fangqing Wen; Junpeng Shi; Guan Gui; Chau Yuen; Hikmet Sari; Fumiyuki Adachi

doi:10.1109/TVT.2024.3408813

Joint DOD and DOA Estimation for NLOS Target Using IRS-Aided Bistatic MIMO Radar

Fangqing Wen, Junpeng Shi, Guan Gui, Chau Yuen, Hikmet Sari, Fumiyuki Adachi

IRIDeS - Resilient EICT Research Promotion Office

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

40 Citations (Scopus)

Abstract

Intelligent Reflecting Surface (IRS) offers new insight into Multiple-Input Multiple-Output (MIMO) radar systems, since it enables a MIMO radar to positioning targets from Non-Line-of-Sight (NLOS) directions. This paper investigates the Direction-of-departure (DOD) and Direction-of-Arrival (DOA) estimation in a bistatic MIMO radar, in which a backward IRS is exploited to receive the echoes reflected by the targets from NLOS viewpoint. A Reduced-Dimension Multiple Signal Classification (MUSIC) estimator is developed. Compared with the state-of-the-art MUSIC and iteratively approximation algorithm, the proposed method RD-MUSIC algorithm is computationally much more efficient. Theoretical analyses are given and numerical results corroborate our analysis.

Original language	English
Pages (from-to)	15798-15802
Number of pages	5
Journal	IEEE Transactions on Vehicular Technology
Volume	73
Issue number	10
DOIs	https://doi.org/10.1109/TVT.2024.3408813
Publication status	Published - 2024

Keywords

IRS
MIMO radar
NLOS
reduced-dimension MUSIC

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10.1109/TVT.2024.3408813

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title = "Joint DOD and DOA Estimation for NLOS Target Using IRS-Aided Bistatic MIMO Radar",

abstract = "Intelligent Reflecting Surface (IRS) offers new insight into Multiple-Input Multiple-Output (MIMO) radar systems, since it enables a MIMO radar to positioning targets from Non-Line-of-Sight (NLOS) directions. This paper investigates the Direction-of-departure (DOD) and Direction-of-Arrival (DOA) estimation in a bistatic MIMO radar, in which a backward IRS is exploited to receive the echoes reflected by the targets from NLOS viewpoint. A Reduced-Dimension Multiple Signal Classification (MUSIC) estimator is developed. Compared with the state-of-the-art MUSIC and iteratively approximation algorithm, the proposed method RD-MUSIC algorithm is computationally much more efficient. Theoretical analyses are given and numerical results corroborate our analysis.",

keywords = "IRS, MIMO radar, NLOS, reduced-dimension MUSIC",

author = "Fangqing Wen and Junpeng Shi and Guan Gui and Chau Yuen and Hikmet Sari and Fumiyuki Adachi",

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T1 - Joint DOD and DOA Estimation for NLOS Target Using IRS-Aided Bistatic MIMO Radar

AU - Wen, Fangqing

AU - Shi, Junpeng

AU - Gui, Guan

AU - Yuen, Chau

AU - Sari, Hikmet

AU - Adachi, Fumiyuki

PY - 2024

Y1 - 2024

N2 - Intelligent Reflecting Surface (IRS) offers new insight into Multiple-Input Multiple-Output (MIMO) radar systems, since it enables a MIMO radar to positioning targets from Non-Line-of-Sight (NLOS) directions. This paper investigates the Direction-of-departure (DOD) and Direction-of-Arrival (DOA) estimation in a bistatic MIMO radar, in which a backward IRS is exploited to receive the echoes reflected by the targets from NLOS viewpoint. A Reduced-Dimension Multiple Signal Classification (MUSIC) estimator is developed. Compared with the state-of-the-art MUSIC and iteratively approximation algorithm, the proposed method RD-MUSIC algorithm is computationally much more efficient. Theoretical analyses are given and numerical results corroborate our analysis.

AB - Intelligent Reflecting Surface (IRS) offers new insight into Multiple-Input Multiple-Output (MIMO) radar systems, since it enables a MIMO radar to positioning targets from Non-Line-of-Sight (NLOS) directions. This paper investigates the Direction-of-departure (DOD) and Direction-of-Arrival (DOA) estimation in a bistatic MIMO radar, in which a backward IRS is exploited to receive the echoes reflected by the targets from NLOS viewpoint. A Reduced-Dimension Multiple Signal Classification (MUSIC) estimator is developed. Compared with the state-of-the-art MUSIC and iteratively approximation algorithm, the proposed method RD-MUSIC algorithm is computationally much more efficient. Theoretical analyses are given and numerical results corroborate our analysis.

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KW - MIMO radar

KW - NLOS

KW - reduced-dimension MUSIC

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Joint DOD and DOA Estimation for NLOS Target Using IRS-Aided Bistatic MIMO Radar

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Keywords

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