基于时频分析的雷达目标识别技术研究

【作者】 潘康；

【导师】 盛卫星；

【作者基本信息】 南京理工大学 ， 通信与信息系统， 2010， 硕士

【摘要】 本论文以空中带微动特性的径向运动目标为研究对象,开展了基于时频分析的高分辨雷达目标识别技术的研究。本文的主要工作有：1.通过改进GRECO建模软件,实现动态RCS计算。添加的目标运动轨迹读取模块,可以满足目标复杂运动的需求,雷达发射波形选择模块使建模软件更加接近真实的雷达系统。并以三种简单目标柱锥、圆锥、球锥作为研究对象,在其径向运动的同时,使其产生旋转、翻滚等微动,用GRECO动态建模软件计算目标的动态RCS。2.对Wigner-Ville变换、短时傅里叶变换(STFT)和小波变换等时频分析方法进行了研究。在MATLAB软件平台上,运用短时傅里叶变换对运动目标的建模回波信号进行了时频分析处理,得到了运动目标回波信号的时频分布图像。按照目标的运动轨迹和姿态制作动画,建立了目标建模与目标识别之间的界面联系。3.提出了一种新的基于时频特征的目标识别算法。运用逐像素扫描算法对目标回波信号的时频分布图像进行特征提取,采用最近邻分类器进行判决分类。同在时频分布图基础上提取矩阵奇异值作为特征进行识别的方法比,本文提出的方法具有更高的正确识别率。仿真试验结果验证了算法的正确性和有效性。更多还原

【Abstract】 In this thesis, focused on the targets in air with micro-movement, radar target recognition based on high resolution time-frequency analysis is studied. The main research work includes:1. GRECO software -a high frequency electromagnetic calculation software, is improved with target movement trajectory processing module and radar emission waveform selection module. Three targets with simple structure, such as cone, sphere and cone, cylinder and cone, are modeled and their dynamic RCS echo signals in different movement are estimated.2. Three time-frequency analysis methods, including the Wigner-Ville transform, short time Fourier transform (STFT) and wavelet transform, are introduced. Dynamic RCS echo signals of movement targets are processed by using short time Fourier transform, and high-resolution time-frequency distribution images are achieved.3. A new radar target recognition method based on time-frequency distribution images is proposed. Pixel scan technique is adopted to extract the feature vector, and the nearest neighbor classifier is used for classification decision. Compared with the target recognition method based on singular value decomposition, the correction probability for recognition of the proposed method is higher. Simulation results verify the correctness and the effectiveness of the proposed method.更多还原