An Object Detection Method for Radar and Image Fusion at Feature Level
ZHANG Ting
REN Mingwu
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.
Keywords：millimeter wave radartarget detectionattentionsensor fusion
Publication Date：2023-11-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 2563-2567 )