基于深度学习的雷达信号目标识别方法研究

Research on radar signal target recognition method based on deep learning

雷达信号目标识别是智能感知领域的重要研究方向。传统方法在处理复杂场景和多目标识别时存在局限性,而深度学习方法以其强大的表达能力和自适应性在雷达信号目标识别中展现出巨大潜力。文章通过综合分析深度学习在雷达信号目标识别中的应用,探讨了数据预处理、深度学习模型选择、目标检测和分类方法、目标跟踪和预测方法以及深度学习与传统方法的融合策略等关键问题,重点讨论了深度学习模型的优化和改进方法。

Radar signal target recognition is an important research direction in the field of intelligent perception.Traditional methods have limitations when dealing with complex scenes and multi-target recognition,while deep learning method shows great potential in radar signal target recognition with its strong expressiveness and adaptability.This paper comprehensively analyzes the application of deep learning in radar signal target recognition,and discusses the key issues such as data preprocessing,deep learning model selection,target detection and classification methods,target tracking and prediction methods,and the fusion strategy of deep learning and traditional methods.At the same time,the optimization and improvement methods of deep learning model are discussed.