河北水利电力学院学报2025，Vol.35Issue(4)：27-32,6.DOI:10.16046/j.cnki.issn2096-5680.2025.04.005
基于LFMCW与图像协同的复杂环境道路目标检测算法研究
Road Object Detection Algorithm in Complex Environments Based on LFMCW and Image Collaboration
摘要
Abstract
Artificial intelligence has been applied to various aspects of life,and the emergence of auton-omous driving technology is a concrete manifestation of artificial intelligence in the automotive field.In or-der to detect complex targets on the road,a target detection algorithm based on linear frequency modula-tion continuous wave and image collaboration is adopted in the study.By analyzing the linear frequency modulation continuous wave and obtaining information on target orientation,distance,and velocity,a tar-get detection model based on the YOLOv7 algorithm is proposed to detect complex targets on the road.The experimental results show that the target detection model has better detection performance for targets with lower speed,closer distance,and smaller angle,demonstrating better detection performance.Selec-ting different iterations to test the performance of the model,when the number of iterations reaches 600,the loss function value of the YOLOv7 algorithm model is 0.05,which is significantly lower than other al-gorithms.关键词
YOLO算法/线性调频连续波/目标检测/SSD算法/图像协同Key words
YOLO algorithm/linear frequency modulation continuous wave/target detection/SSD al-gorithm/image collaboration分类
信息技术与安全科学引用本文复制引用
张飞..基于LFMCW与图像协同的复杂环境道路目标检测算法研究[J].河北水利电力学院学报,2025,35(4):27-32,6.基金项目
安徽省教育厅重点项目(2023AH052418) （2023AH052418）
