稀疏分解与提升小波变换相结合的雷达脉冲参数估计法  

Estimation of radar pulse parameters based on sparse decomposition and lifting wavelet transform

作　　者：薛坚[1,2] 黄桂根 Xue Jian;Huang Guigen(Nanjing Research Institute of Electronics Technology,Nanjing 210039,China;School of Electronic Science and Engineering,Nanjing University,Nanjing 210023,China)

机构地区：[1]南京电子技术研究所,南京210039 [2]南京大学电子科学与工程学院,南京210023

出　　处：《电子测量技术》2020年第16期109-113,共5页Electronic Measurement Technology

基　　金：国家自然科学基金项目(61976113)资助。

摘　　要：电子侦察领域中,雷达脉冲参数的正确测量是信号分选和辐射源识别的基础。针对复杂电磁环境中传统参数测量方法可靠性下降问题,提出了一种将稀疏分解与提升小波变换相结合的雷达脉冲参数测量方法。首先介绍了接收信号的模型和参数测量的原理。然后引入稀疏分解理论和提升小波变换,分别对传统频率和到达时间的测量方法进行改进,给出了改进频率和到达时间测量的处理流程。最后给出了仿真实验,实验结果验证了方法的有效性和正确性,在较低信噪比的情况下也有较高的估计精度。In the field of electron reconnaissance,correct estimation of radar pulse parameters is the key to signal sorting and radar emitter identification. Aiming at the problem that the reliability of the typical parameter estimation methods is falling in complex electromagnetic environment, a new radar pulse parameters estimation method based on sparse decomposition and lifting wavelet transform is proposed. Firstly the model of the received pulse train and the principle of parameters estimation are introduced. Then sparse decomposition theory and lifting wavelet transform are introduced to improve the traditional frequency and arrival time estimation methods, the improved processing methods of each parameter are given. Finally simulation experiments are present to check the effectiveness of the proposed method. From simulations it can be seen that the proposed method can achieve the satisfactory results. It also has the higher estimation accuracy in low signal-to-noise ratio(SNR).

关 键 词：电子侦察 稀疏分解 提升小波变换 参数测量 

分 类 号：TN971[电子电信—信号与信息处理]