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Open AccessArticle
Single-Snapshot Direction of Arrival Estimation for Vehicle-Mounted Millimeter-Wave Radar via Fast Deterministic Maximum Likelihood Algorithm
by
Hong Liu
Hong Liu 1,*,†,
Han Xie
Han Xie 1,†,
Zhen Wang
Zhen Wang 2,
Xianling Wang
Xianling Wang 1 and
Donghang Chai
Donghang Chai 1
1
School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen 361000, China
2
China Automotive Innovation Corporation, Nanjing 211100, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
World Electr. Veh. J. 2024, 15(7), 321; https://doi.org/10.3390/wevj15070321 (registering DOI)
Submission received: 15 June 2024
/
Revised: 15 July 2024
/
Accepted: 18 July 2024
/
Published: 20 July 2024
Abstract
As one of the fundamental vehicular perception technologies, millimeter-wave radar’s accuracy in angle measurement affects the decision-making and control of vehicles. In order to enhance the accuracy and efficiency of the Direction of Arrival (DoA) estimation of radar systems, a super-resolution angle measurement strategy based on the Fast Deterministic Maximum Likelihood (FDML) algorithm is proposed in this paper. This strategy sequentially uses Digital Beamforming (DBF) and Deterministic Maximum Likelihood (DML) in the Field of View (FoV) to perform a rough search and precise search, respectively. In a simulation with a signal-to-noise ratio of 20 dB, FDML can accurately determine the target angle in just 16.8 ms, with a positioning error of less than 0.7010. DBF, the Iterative Adaptive Approach (IAA), DML, Fast Iterative Adaptive Approach (FIAA), and FDML are subjected to simulation with two targets, and their performance is compared in this paper. The results demonstrate that under the same angular resolution, FDML reduces computation time by and angle measurement error by compared with the angular measurement results of two targets. The FDML algorithm significantly improves computational efficiency while ensuring measurement performance. It provides more reliable technical support for autonomous vehicles and lays a solid foundation for the advancement of autonomous driving technology.
Share and Cite
MDPI and ACS Style
Liu, H.; Xie, H.; Wang, Z.; Wang, X.; Chai, D.
Single-Snapshot Direction of Arrival Estimation for Vehicle-Mounted Millimeter-Wave Radar via Fast Deterministic Maximum Likelihood Algorithm. World Electr. Veh. J. 2024, 15, 321.
https://doi.org/10.3390/wevj15070321
AMA Style
Liu H, Xie H, Wang Z, Wang X, Chai D.
Single-Snapshot Direction of Arrival Estimation for Vehicle-Mounted Millimeter-Wave Radar via Fast Deterministic Maximum Likelihood Algorithm. World Electric Vehicle Journal. 2024; 15(7):321.
https://doi.org/10.3390/wevj15070321
Chicago/Turabian Style
Liu, Hong, Han Xie, Zhen Wang, Xianling Wang, and Donghang Chai.
2024. "Single-Snapshot Direction of Arrival Estimation for Vehicle-Mounted Millimeter-Wave Radar via Fast Deterministic Maximum Likelihood Algorithm" World Electric Vehicle Journal 15, no. 7: 321.
https://doi.org/10.3390/wevj15070321
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