干扰识别和抑制增强的通信感知融合数据集
收藏资源简介：
实现通信抗干扰能力/可靠性提升50%，通感干扰残余小于3dB，数字抑制达到30dB，速率或感知精度提高1倍。包含干扰识别和抑制训练数据集，用于训练干扰识别和抑制网络；用于智能干扰管理仿真平台的深度学习干扰识别和抑制网络模型数据。项目在实验室展开，在数据采集和加工过程中，遵循面向通-感-算一体化的智能协同干扰管理技术实验环境规范。参与人员均有智能干扰管理学习基础，项目执行过程中，定期组织会议讨论面向通-感-算一体化的智能协同干扰管理技术的相关内容。项目建立了较为完备的数据资源质量控制措施，制定了项目管理相关文件，进一步规范和加强了项目管理，促进了数据资源产生全过程的质量管理控制，保证了本项目汇交科学数据的来源、采集、加工、处理等各环节的有序进行，有效保障了科学数据的质量。
This dataset enables a 50% improvement in communication anti-jamming capability and reliability, with residual communication-sensing interference less than 3 dB, digital suppression reaching 30 dB, and doubled data rate or sensing accuracy. It contains training datasets for interference recognition and suppression, which are used to train interference recognition and suppression networks, and also provides data for deep learning-based interference recognition and suppression network models applied to intelligent interference management simulation platforms. This project is conducted in a laboratory, and during data collection and processing, it complies with the specifications of the experimental environment for intelligent collaborative interference management technology oriented to integrated communication-sensing-computing. All project members have a foundational background in intelligent interference management. Regular meetings are held during project execution to discuss topics related to intelligent collaborative interference management technology oriented to integrated communication-sensing-computing. The project has established relatively comprehensive data resource quality control measures, formulated relevant project management documents to further standardize and strengthen project management, promoted quality management and control across the entire lifecycle of data resource generation, ensured the orderly execution of all links including the source, collection, processing, and handling of the scientific data submitted by this project, and effectively guaranteed the quality of the scientific data.
