摘 要
随着现代电子信息工程的快速发展，雷达信号处理技术作为关键领域之一，在目标检测、跟踪及识别等方面发挥着不可替代的作用。本研究以提升雷达信号处理性能为目标，针对复杂电磁环境下信号处理面临的挑战展开深入探讨。通过引入先进的数学模型与算法优化方法，提出了一种基于深度学习的自适应信号处理框架，该框架能够有效应对非平稳信号和噪声干扰问题。研究中设计并实现了多维特征提取算法，结合卷积神经网络对雷达回波信号进行精准分类与参数估计，显著提高了系统的抗噪能力和分辨率。实验结果表明，所提方法在低信噪比条件下仍能保持较高的检测精度，相较于传统方法具有明显优势。此外，本研究还开发了实时信号处理平台，验证了算法的实际应用价值。总体而言，本研究不仅为复杂环境下的雷达信号处理提供了新思路，还推动了电子信息工程领域的技术创新与发展，为未来智能化雷达系统的设计奠定了理论和技术基础。
关键词：雷达信号处理 深度学习 自适应框架
Abstract
With the rapid development of modern electronic information engineering, radar signal processing technology, as one of the key areas, plays an irreplaceable role in target detection, tracking, and recognition. This study aims to enhance the performance of radar signal processing by addressing the challenges faced in complex electromagnetic environments. By incorporating advanced mathematical models and algorithm optimization methods, an adaptive signal processing fr amework based on deep learning is proposed, which effectively tackles non-stationary signals and noise interference issues. A multidimensional feature extraction algorithm is designed and implemented in this research, combining convolutional neural networks for accurate classification and parameter estimation of radar echo signals, thereby significantly improving the system's noise resistance and resolution. Experimental results demonstrate that the proposed method maintains high detection accuracy even under low signal-to-noise ratio conditions, showing obvious advantages over traditional approaches. Furthermore, a real-time signal processing platform has been developed in this study to validate the practical application value of the algorithms. Overall, this research not only provides new insights into radar signal processing in complex environments but also promotes technological innovation and development in the field of electronic information engineering, laying a theoretical and technical foundation for the design of future intelligent radar systems.
Keyword:Radar Signal Processing Deep Learning Adaptive fr amework
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状分析 1
1.3本文研究方法概述 1
2雷达信号处理基础理论 2
2.1雷达信号处理基本原理 2
2.2常用信号处理算法综述 2
2.3电子信息工程中的关键技术需求 3
3雷达信号检测与估计技术 3
3.1信号检测理论及其应用 3
3.2参数估计方法研究 4
3.3检测与估计性能评估 4
4高级雷达信号处理技术研究 5
4.1自适应信号处理技术 5
4.2多目标跟踪算法分析 5
4.3抗干扰技术研究与实现 6
结论 6
参考文献 8
致谢 9
随着现代电子信息工程的快速发展，雷达信号处理技术作为关键领域之一，在目标检测、跟踪及识别等方面发挥着不可替代的作用。本研究以提升雷达信号处理性能为目标，针对复杂电磁环境下信号处理面临的挑战展开深入探讨。通过引入先进的数学模型与算法优化方法，提出了一种基于深度学习的自适应信号处理框架，该框架能够有效应对非平稳信号和噪声干扰问题。研究中设计并实现了多维特征提取算法，结合卷积神经网络对雷达回波信号进行精准分类与参数估计，显著提高了系统的抗噪能力和分辨率。实验结果表明，所提方法在低信噪比条件下仍能保持较高的检测精度，相较于传统方法具有明显优势。此外，本研究还开发了实时信号处理平台，验证了算法的实际应用价值。总体而言，本研究不仅为复杂环境下的雷达信号处理提供了新思路，还推动了电子信息工程领域的技术创新与发展，为未来智能化雷达系统的设计奠定了理论和技术基础。
关键词：雷达信号处理 深度学习 自适应框架
Abstract
With the rapid development of modern electronic information engineering, radar signal processing technology, as one of the key areas, plays an irreplaceable role in target detection, tracking, and recognition. This study aims to enhance the performance of radar signal processing by addressing the challenges faced in complex electromagnetic environments. By incorporating advanced mathematical models and algorithm optimization methods, an adaptive signal processing fr amework based on deep learning is proposed, which effectively tackles non-stationary signals and noise interference issues. A multidimensional feature extraction algorithm is designed and implemented in this research, combining convolutional neural networks for accurate classification and parameter estimation of radar echo signals, thereby significantly improving the system's noise resistance and resolution. Experimental results demonstrate that the proposed method maintains high detection accuracy even under low signal-to-noise ratio conditions, showing obvious advantages over traditional approaches. Furthermore, a real-time signal processing platform has been developed in this study to validate the practical application value of the algorithms. Overall, this research not only provides new insights into radar signal processing in complex environments but also promotes technological innovation and development in the field of electronic information engineering, laying a theoretical and technical foundation for the design of future intelligent radar systems.
Keyword:Radar Signal Processing Deep Learning Adaptive fr amework
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状分析 1
1.3本文研究方法概述 1
2雷达信号处理基础理论 2
2.1雷达信号处理基本原理 2
2.2常用信号处理算法综述 2
2.3电子信息工程中的关键技术需求 3
3雷达信号检测与估计技术 3
3.1信号检测理论及其应用 3
3.2参数估计方法研究 4
3.3检测与估计性能评估 4
4高级雷达信号处理技术研究 5
4.1自适应信号处理技术 5
4.2多目标跟踪算法分析 5
4.3抗干扰技术研究与实现 6
结论 6
参考文献 8
致谢 9
