计算机与数字工程2023，Vol.51Issue(11)：2563-2567,5.DOI:10.3969/j.issn.1672-9722.2023.11.017
一种毫米波雷达和图像特征级融合的目标检测方法
An Object Detection Method for Radar and Image Fusion at Feature Level
张婷 1任明武1
作者信息
- 1. 南京理工大学计算机科学与工程学院 南京 210094
- 折叠
摘要
Abstract
In order to alleviate the limitations of object detection based on a single sensor in complex scenes,the paper propos-es an object detection method(SPCRF-Net)based on millimeter wave radar and image at feature-level fusion.This method prepro-cesses radar raw data into fixed-size line segments and maps them to the image,and introduces pyramid pooling to process radar da-ta.And then this method uses VGG16 as the backbone for image feature extraction,and integrates radar features and image features in each layer.In the fusion level,the SE attention module is introduced to enhance the ability of high-level feature perception,and a fusion structure(PFPN)is constructed to enhance feature extraction.Experiments show that this method can effectively reduce the missed detection of targets and can improve the performance of object detection.关键词
毫米波雷达/目标检测/注意力/传感器融合Key words
millimeter wave radar/target detection/attention/sensor fusion分类
信息技术与安全科学引用本文复制引用
张婷,任明武..一种毫米波雷达和图像特征级融合的目标检测方法[J].计算机与数字工程,2023,51(11):2563-2567,5.
