Low-Complexity High-Resolution Parameter Estimation for Automotive MIMO Radars

Yu Chien Lin; Ta-Sung Lee; Yun Han Pan; Kuan Heng Lin

doi:10.1109/ACCESS.2019.2926413

Low-Complexity High-Resolution Parameter Estimation for Automotive MIMO Radars

Yu Chien Lin, Ta-Sung Lee, Yun Han Pan, Kuan Heng Lin

研究成果: Article › 同行評審

26 引文斯高帕斯（Scopus）

摘要

In this paper, we propose a parameter estimation method for multiple-input-multiple-output (MIMO) automotive radars that consists of two stages. The first stage is a low-complexity three-dimensional (3D) constant false alarm rate (CFAR) detection technique that exploits spatial filtering to extend radar coverage, and it performs low-complexity peak detection. The second stage is an ESPRIT-based direction-of-arrival (DOA) estimation technique that adopts time-frequency resource division to generate high-quality snapshots and it performs DOA estimation of targets without the knowledge of the target number. Computer simulations reveal that the proposed method achieves the performance of the two-dimensional ordered statistic CFAR (2D OS-CFAR) while having much lower computational complexity, and it offers the higher resolution DOA estimation compared to the conventional MIMO radars.

原文	English
文章編號	8753573
頁（從 - 到）	16127-16138
頁數	12
期刊	IEEE Access
卷	8
DOIs	https://doi.org/10.1109/ACCESS.2019.2926413
出版狀態	Published - 2 7月 2019

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10.1109/ACCESS.2019.2926413

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引用此

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title = "Low-Complexity High-Resolution Parameter Estimation for Automotive MIMO Radars",

abstract = "In this paper, we propose a parameter estimation method for multiple-input-multiple-output (MIMO) automotive radars that consists of two stages. The first stage is a low-complexity three-dimensional (3D) constant false alarm rate (CFAR) detection technique that exploits spatial filtering to extend radar coverage, and it performs low-complexity peak detection. The second stage is an ESPRIT-based direction-of-arrival (DOA) estimation technique that adopts time-frequency resource division to generate high-quality snapshots and it performs DOA estimation of targets without the knowledge of the target number. Computer simulations reveal that the proposed method achieves the performance of the two-dimensional ordered statistic CFAR (2D OS-CFAR) while having much lower computational complexity, and it offers the higher resolution DOA estimation compared to the conventional MIMO radars.",

keywords = "CFAR detection, DOA estimation, ESPRIT, MIMO radar, mmWave radar",

author = "Lin, {Yu Chien} and Ta-Sung Lee and Pan, {Yun Han} and Lin, {Kuan Heng}",

year = "2019",

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AU - Lin, Yu Chien

AU - Lee, Ta-Sung

AU - Pan, Yun Han

AU - Lin, Kuan Heng

PY - 2019/7/2

Y1 - 2019/7/2

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AB - In this paper, we propose a parameter estimation method for multiple-input-multiple-output (MIMO) automotive radars that consists of two stages. The first stage is a low-complexity three-dimensional (3D) constant false alarm rate (CFAR) detection technique that exploits spatial filtering to extend radar coverage, and it performs low-complexity peak detection. The second stage is an ESPRIT-based direction-of-arrival (DOA) estimation technique that adopts time-frequency resource division to generate high-quality snapshots and it performs DOA estimation of targets without the knowledge of the target number. Computer simulations reveal that the proposed method achieves the performance of the two-dimensional ordered statistic CFAR (2D OS-CFAR) while having much lower computational complexity, and it offers the higher resolution DOA estimation compared to the conventional MIMO radars.

KW - CFAR detection

KW - DOA estimation

KW - ESPRIT

KW - MIMO radar

KW - mmWave radar

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Low-Complexity High-Resolution Parameter Estimation for Automotive MIMO Radars

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