太赫兹科学与电子信息学报2024，Vol.22Issue(2)：132-141,10.DOI:10.11805/TKYDA2023170
基于DB-YOLO的双基地雷达弱运动目标检测方法
Bistatic radar weak moving target detection method based on DB-YOLO
摘要
Abstract
Non-cooperative bistatic radar has a low signal-to-noise ratio in the echo due to its special detection method.In particular,the detection between frames in the radar scanning cycle for maritime moving targets is not stable,which will bring great difficulties for subsequent target tracking.The low threshold Constant False Alarm Rate(CFAR)detector is employed to match the detection results of radar range-Doppler dimension and range-azimuth dimension to obtain the corresponding mask map,and the potential moving targets are found.Then,a Double Backbone-YOLO(DB-YOLO)that fuses multi-dimensional feature information is proposed.The network adopts a dual-trunk structure,extracts the features of the moving target mask map and the same-scale P-display map under its mapping,and uses a deep separable convolution module to reduce the model parameters of the network.Finally,the comparison experiments with Faster RCNN,YOLOv5 and its common variant YOLOv5-ConvNeXt show that DB-YOLO effectively improves the target detection performance and ensures the inference speed,which lays a foundation for target tracking of noncooperative bistatic radar.关键词
非合作双基地雷达/目标检测/双主干YOLO/特征融合Key words
non-cooperative bistatic radar/target detection/DB-YOLO/feature fusion分类
信息技术与安全科学引用本文复制引用
陆源,宋杰,熊伟,陈小龙..基于DB-YOLO的双基地雷达弱运动目标检测方法[J].太赫兹科学与电子信息学报,2024,22(2):132-141,10.基金项目
国家自然科学基金资助项目(61971433) （61971433）
山东省泰山学者计划资助项目(tsqn202211247) （tsqn202211247）
