Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey

Multi-modal fusion is imperative to the implementation of reliable object detection and tracking in complex environments. Exploiting the synergy of heterogeneous modal information endows perception systems the ability to achieve more comprehensive, robust, and accurate performance. As a nucleus concern in wireless-vision collaboration, radar-camera fusion has prompted prospective research directions owing to its extensive applicability, complementarity, and compatibility. Nonetheless, there still lacks a systematic survey specifically focusing on deep fusion of radar and camera for object detection and tracking. To fill this void, we embark on an endeavor to comprehensively review radar-camera fusion in a holistic way. First, we elaborate on the fundamental principles, methodologies, and applications of radar-camera fusion perception. Next, we delve into the key techniques concerning sensor calibration, modal representation, data alignment, and fusion operation. Furthermore, we provide a detailed taxonomy covering the research topics related to object detection and tracking in the context of radar and camera technologies. Finally, we discuss the emerging perspectives in the field of radar-camera fusion perception and highlight the potential areas for future research.

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Publication Details

Journal
IEEE Communications Surveys & Tutorials
Published
2025-08-18
DOI
https://doi.org/10.1109/comst.2025.3599596
Citations
13
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
64.92
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article

Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey

Zehui Xiong, Chen An-jun, Shibo He, Jun Luo et al.
13 citations
IEEE Communications Surveys & Tutorials
Infrared Target Detection Methodologies
64.92
article

Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey

Zehui Xiong, Chen An-jun, Shibo He, Jun Luo, Jiming Chen, Kun Shi, Zhenyu Shi
article en
13 citations

Abstract

Multi-modal fusion is imperative to the implementation of reliable object detection and tracking in complex environments. Exploiting the synergy of heterogeneous modal information endows perception systems the ability to achieve more comprehensive, robust, and accurate performance. As a nucleus concern in wireless-vision collaboration, radar-camera fusion has prompted prospective research directions owing to its extensive applicability, complementarity, and compatibility. Nonetheless, there still lacks a systematic survey specifically focusing on deep fusion of radar and camera for object detection and tracking. To fill this void, we embark on an endeavor to comprehensively review radar-camera fusion in a holistic way. First, we elaborate on the fundamental principles, methodologies, and applications of radar-camera fusion perception. Next, we delve into the key techniques concerning sensor calibration, modal representation, data alignment, and fusion operation. Furthermore, we provide a detailed taxonomy covering the research topics related to object detection and tracking in the context of radar and camera technologies. Finally, we discuss the emerging perspectives in the field of radar-camera fusion perception and highlight the potential areas for future research.

IEEE Communications Surveys & TutorialsVol. 28
Singapore University of Technology and Design (SG), Nanyang Technological University (SG), State Key Laboratory of Industrial Control Technology (CN)
Openalex Percentile: Top 0%
Infrared Target Detection Methodologies
64.92
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