摘要
针对传统方法不适用于欠采样条件下线性调频(LFM)信号在低信噪比(SNR)条件下带宽估计问题,提出一种基于分布式压缩感知(DCS)的带宽估计方法,利用同一信源多个脉冲的联合稀疏特性进行LFM信号带宽估计。首先构建LFM欠采样信号模型,其次利用DCS算法对LFM带宽进行联合稀疏重构,然后分析了所提LFM信号带宽估计方法性能,最后利用仿真验证了方法的可行性和有效性。
Aiming at the problem that traditional methods cannot estimate the bandwidth of undersampled Linear Frequency Modulation(LFM)signals under low Signal Noise Ratio(SNR),a bandwidth estimation method based on Distributed Compressive Sensing(DCS)is proposed,which uses the joint sparse characteristics of multiple LFM signals with the same modulation type from the same source to estimate the bandwidth of LFM signal.Firstly,the under-sampled LFM signal model is constructed.Secondly,the LFM bandwidth is reconstructed by DCS algorithm.Then the parameter estimation ability of the proposed method under low SNR conditions is analyzed.Finally,the feasibility and validity of the proposed method are verified by simulation.
作者
陈梁栋
李梦瑶
刘昕卓
CHEN Liangdong;LI Mengyao;LIU Xinzhuo(Unit 95438 of the PLA,Pengshan Sichuan 620860,China;Unit 78110 of the PLA,Chengdu Sichuan 610000,China)
出处
《太赫兹科学与电子信息学报》
北大核心
2020年第5期797-801,共5页
Journal of Terahertz Science and Electronic Information Technology
关键词
欠采样
线性调频信号
分布式压缩感知
带宽估计
under-sampling
Linear Frequency Modulation signal
Distributed Compressive Sensing
bandwidth estimation
