电气技术2025，Vol.26Issue(6)：29-37,44,10.
一种基于雷达和相机数据融合网络的输电线路鸟类多目标识别方法
A multi-target bird recognition method for transmission lines based on radar and camera data fusion
范程涛 1高伟 1靳小喜2
作者信息
- 1. 福州大学电气工程与自动化学院,福州 350108
- 2. 福州电力设计院有限公司,福州 350007
- 折叠
摘要
Abstract
This paper proposes a multi-target recgnition network for birds on power transmission lines,called RVFNet,based on the fusion of radar and camera data.The network achieves high-precision recgnition of bird targets within the monitoring range by integrating radar radio frequency(RF)data with visual images.To address the semantic differences between multimodal data,the correspondence between radar RF signals and image positional information is calculated to ensure consistency in feature representation.Structurally,the network incorporates a bird posture convolutional network(BPC)to effectively fuse multimodal information,enhancing the extraction of small-target features and preserving fine details.Additionally,a feature fusion module(FFM)is introduced to integrate multimodal features,significantly improving feature interaction while maintaining low computational costs.Experimental results demonstrate that RVFNet achieves an average bird recognition accuracy of 80.18%under various weather conditions,highlighting its robustness.关键词
探鸟驱鸟/视觉图像/雷达射频图像/传感器融合/深度卷积神经网络Key words
identify and repel birds/visual images/radar radio frequency images/sensor fusion/deep convolutional neural networks引用本文复制引用
范程涛,高伟,靳小喜..一种基于雷达和相机数据融合网络的输电线路鸟类多目标识别方法[J].电气技术,2025,26(6):29-37,44,10.
