雷达
极高频率
人工智能
传感器融合
计算机科学
计算机视觉
职位(财务)
雷达工程细节
雷达成像
遥感
融合
过程(计算)
地理
电信
操作系统
哲学
经济
语言学
财务
作者
Yong Zhou,Yanyan Dong,Fujin Hou,Jianqing Wu
出处
期刊:Sustainability
[MDPI AG]
日期:2022-04-24
卷期号:14 (9): 5114-5114
被引量:14
摘要
Cameras allow for highly accurate identification of targets. However, it is difficult to obtain spatial position and velocity information about a target by relying solely on images. The millimeter-wave radar (MMW radar) sensor itself easily acquires spatial position and velocity information of the target but cannot identify the shape of the target. MMW radar and camera, as two sensors with complementary strengths, have been heavily researched in intelligent transportation. This article examines and reviews domestic and international research techniques for the definition, process, and data correlation of MMW radar and camera fusion. This article describes the structure and hierarchy of MMW radar and camera fusion, it also presents its fusion process, including spatio-temporal alignment, sensor calibration, and data information correlation methods. The data fusion algorithms from MMW radar and camera are described separately from traditional fusion algorithms and deep learning based algorithms, and their advantages and disadvantages are briefly evaluated.
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