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欠采样条件下基于DCS的LFM信号参数估计方法
Parameter Estimation Method of LFM Signal Based on DCS under Unsampled Conditions
投稿时间:2019-03-17  修订日期:2019-07-03
中文关键词:欠采样  线性调频信号  分布式压缩感知  参数估计
英文关键词:Undersampling  LFM signal  Distributed Compressive Sensing  Parameter estimation
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作者单位E-mail
陈梁栋  13476810127@163.com 
李梦瑶   
刘昕卓   
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中文摘要:
      针对传统方法不适用于欠采样条件下线性调频(Linear Frequency Modulation, LFM)信号在低信噪比条件下带宽估计问题,本文提出了一种基于分布式压缩感知(Distributed Compressive Sensing, DCS)的参数估计方法,利用多个相同调制类型的LFM信号的联合稀疏特性进行信号带宽估计。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,然后分析了所提方法在低信噪比条件下的参数估计能力,最后利用仿真验证了方法的可行性和有效性。
英文摘要:
      Aiming at the problem that traditional methods can’t estimate the bandwidth of under-sampled LFM signals under low SNR, a parameter estimation method based on distributed compressed sensing (DCS) is proposed, which uses the joint sparse characteristics of multiple LFM signals of the same modulation type to estimate the bandwidth of LFM signal. Firstly, the undersampled 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.
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