摘 要
随着电子信息工程的快速发展，雷达信号处理技术在目标检测、跟踪和识别等领域的重要性日益凸显。本研究旨在深入探讨现代雷达信号处理的关键技术及其在复杂电磁环境中的应用，以提升雷达系统的性能和适应性。研究基于先进的数学建模与算法设计方法，重点分析了自适应波束形成、稀疏信号重建以及多目标跟踪等核心技术，并结合实际应用场景提出了改进的信号处理策略。通过引入深度学习框架优化传统算法，显著提高了雷达系统在低信噪比条件下的目标分辨能力和抗干扰性能。实验结果表明，所提出的算法在复杂场景中展现出更高的鲁棒性和效率，特别是在杂波抑制和小目标检测方面取得了突破性进展。本研究的主要贡献在于将人工智能技术与传统雷达信号处理深度融合，为未来智能化雷达系统的设计提供了新思路，同时为相关领域的理论研究和技术应用奠定了坚实基础。
关键词：雷达信号处理 深度学习 自适应波束形成
Abstract
With the rapid development of electronic information engineering, radar signal processing technology has become increasingly significant in areas such as target detection, tracking, and recognition. This study focuses on exploring the key technologies of modern radar signal processing and their applications in complex electromagnetic environments to enhance the performance and adaptability of radar systems. Based on advanced mathematical modeling and algorithm design methodologies, this research conducts an in-depth analysis of core technologies including adaptive beamforming, sparse signal reconstruction, and multi-target tracking, while proposing improved signal processing strategies tailored to practical application scenarios. By integrating deep learning fr ameworks to optimize traditional algorithms, a notable improvement in target resolution and interference resistance capabilities under low signal-to-noise ratio conditions is achieved. Experimental results demonstrate that the proposed algorithms exhibit superior robustness and efficiency in complex scenarios, particularly achieving breakthroughs in clutter suppression and small target detection. The primary contribution of this study lies in the deep integration of artificial intelligence techniques with conventional radar signal processing, providing new insights for the design of future intelligent radar systems and establishing a solid foundation for theoretical research and technical applications in related fields.
Keyword:Radar Signal Processing Deep Learning Adaptive Beamforming
目 录
1绪论 1
1.1雷达信号处理技术的研究背景 1
1.2雷达信号处理技术的研究意义 1
1.3国内外研究现状与发展趋势 1
1.4本文研究方法与主要内容 2
2雷达信号处理基础理论分析 2
2.1雷达信号的基本特性与分类 2
2.2常用信号处理算法概述 2
2.3雷达信号处理中的数学模型 3
2.4电子信息工程对雷达信号处理的要求 3
3雷达信号检测与参数估计技术研究 4
3.1雷达信号检测原理与方法 4
3.2参数估计的理论基础 4
3.3现代检测与估计技术的应用 5
3.4检测与估计性能评估指标 5
4高分辨率雷达信号处理技术研究 6
4.1高分辨率信号处理的意义与挑战 6
4.2脉冲压缩技术及其优化 6
4.3合成孔径雷达信号处理方法 7
4.4高分辨率技术的实际应用案例 7
结论 8
参考文献 9
致谢 10
随着电子信息工程的快速发展，雷达信号处理技术在目标检测、跟踪和识别等领域的重要性日益凸显。本研究旨在深入探讨现代雷达信号处理的关键技术及其在复杂电磁环境中的应用，以提升雷达系统的性能和适应性。研究基于先进的数学建模与算法设计方法，重点分析了自适应波束形成、稀疏信号重建以及多目标跟踪等核心技术，并结合实际应用场景提出了改进的信号处理策略。通过引入深度学习框架优化传统算法，显著提高了雷达系统在低信噪比条件下的目标分辨能力和抗干扰性能。实验结果表明，所提出的算法在复杂场景中展现出更高的鲁棒性和效率，特别是在杂波抑制和小目标检测方面取得了突破性进展。本研究的主要贡献在于将人工智能技术与传统雷达信号处理深度融合，为未来智能化雷达系统的设计提供了新思路，同时为相关领域的理论研究和技术应用奠定了坚实基础。
关键词：雷达信号处理 深度学习 自适应波束形成
Abstract
With the rapid development of electronic information engineering, radar signal processing technology has become increasingly significant in areas such as target detection, tracking, and recognition. This study focuses on exploring the key technologies of modern radar signal processing and their applications in complex electromagnetic environments to enhance the performance and adaptability of radar systems. Based on advanced mathematical modeling and algorithm design methodologies, this research conducts an in-depth analysis of core technologies including adaptive beamforming, sparse signal reconstruction, and multi-target tracking, while proposing improved signal processing strategies tailored to practical application scenarios. By integrating deep learning fr ameworks to optimize traditional algorithms, a notable improvement in target resolution and interference resistance capabilities under low signal-to-noise ratio conditions is achieved. Experimental results demonstrate that the proposed algorithms exhibit superior robustness and efficiency in complex scenarios, particularly achieving breakthroughs in clutter suppression and small target detection. The primary contribution of this study lies in the deep integration of artificial intelligence techniques with conventional radar signal processing, providing new insights for the design of future intelligent radar systems and establishing a solid foundation for theoretical research and technical applications in related fields.
Keyword:Radar Signal Processing Deep Learning Adaptive Beamforming
目 录
1绪论 1
1.1雷达信号处理技术的研究背景 1
1.2雷达信号处理技术的研究意义 1
1.3国内外研究现状与发展趋势 1
1.4本文研究方法与主要内容 2
2雷达信号处理基础理论分析 2
2.1雷达信号的基本特性与分类 2
2.2常用信号处理算法概述 2
2.3雷达信号处理中的数学模型 3
2.4电子信息工程对雷达信号处理的要求 3
3雷达信号检测与参数估计技术研究 4
3.1雷达信号检测原理与方法 4
3.2参数估计的理论基础 4
3.3现代检测与估计技术的应用 5
3.4检测与估计性能评估指标 5
4高分辨率雷达信号处理技术研究 6
4.1高分辨率信号处理的意义与挑战 6
4.2脉冲压缩技术及其优化 6
4.3合成孔径雷达信号处理方法 7
4.4高分辨率技术的实际应用案例 7
结论 8
参考文献 9
致谢 10
