The Application of Fusion of Millimeter-Wave Radar and Image Sensors in Intelligent Driving

Shurui Liu

doi:10.54097/4twn6z05

Authors

Shurui Liu

DOI:

https://doi.org/10.54097/4twn6z05

Keywords:

Multi-sensor fusion; Intelligent driving; Millimeter-wave radar; Image sensors.

Abstract

In the field of intelligent driving, multi-sensor fusion has been applied to many systems. With the rapid advancement of autonomous driving technologies, environmental perception and high-precision positioning have become critical for enhancing vehicle safety and operational efficiency. The growing complexity of urban traffic scenarios further necessitates robust and redundant sensing systems to ensure reliability under diverse conditions. According to the fact that millimeter-wave radar and image sensors are widely equipped on vehicles, this essay summarizes the main concepts of intelligent driving and multi-sensor fusion, while analyzing the factor graph optimization algorithm and fusion network model applied to the fusion positioning of millimeter-wave radar and image sensor, with discussions on the application of multi-sensor fusion in achieving precise positioning functions for auxiliary intelligent driving systems. At the same time, the essay also discusses the shortcomings of intelligent driving systems used in contemporary vehicles. Therefore, researching the fusion technology of millimeter-wave radar and image sensors holds significant theoretical value and practical importance for enhancing environmental perception accuracy and driving safety.

References

[1]Ruan Yaoting, Liu Sizhong, Li Jiwei, et al. Research on key technologies of intelligent driving[J]. Automation application, 2025,66(06):74-79.

[2]Zhang Linzhong. Application and Analysis of Autonomous Driving Technology Based on Multi-sensor Fusion Technology[J]. Information and Computer, 2025,37(10):148-150.

[3]Tang Wenwen, Dai Qiang, Liu Jun, et al. Journal of Southwest University of Science and Technology,2024,39(03):96-102.

[4]She Yuhang. Research on Machine Vision and Millimeter-wave Radar Fusion Perception Algorithm[D]. Central China Normal University,2023.

[5]Cao Y L, Wang N F, Xiao C W, et al. Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks [EB/OL]. (2021-06-17)[2025-08-20].

[6]Song Xiaohong, Chen Baifan. Research on the application of multi-sensor information fusion in intelligent cars[J]. computer simulation, 2012,29(06):320-322+368.

[7]Zhang Wei, Li Xudong, Cao Wei, et al. multi-sensor fusion positioning method for intelligent vehicles based on graph optimization[J]. Software engineering2025,28(04):53-56+72.

[8]Wang Z, Wu Y, Niu Q. Multi-sensor fusion in automated driving: A survey[J]. Ieee Access, 2019, 8: 2847-2868.

[9]Jiang Fengyang, Cheng Yao, Han Zhe, et al. Multi-sensor Fusion for Indoor and Outdoor Mapping and Localization Based on LVI-SAM-Stereo[J/OL]. Journal of Shandong University (Engineering Science), 1-12[2025-07-21].

[10]Tong R, Jiang Q, Zou Z, et al. Embedded system vehicle based on multi-sensor fusion[J]. IEEE Access, 2023, 11: 50334-50349.