摘要
针对当前多径线性调频(LFM)信号参数估计中存在的精度低、依赖高信噪比等问题,提出了一种基于压缩感知的多径LFM信号参数估计新方法。通过将包含多径分量的LFM信号稀疏分解与重构,实现了多径分量时延及衰减的参数估计。新方法突破了传统Nyquist采样定理的限制,可利用较少数据恢复信号。仿真实验证明了该方法的有效性,并通过与传统方法的性能比较,证实新方法具有更高的时延分辨率、数据资源利用率且可以达到较高的估计精度。
Due to the disadvantage of low precision and high reliance upon good SNR in the current methods,a novel algorithm of parameter estimation is proposed for multipath LFM signal based on compressive sensing（CS）.Time-delay and attenuation of LFM signal multipath component is estimated by sparse decomposing and reconstructing the signals with multipath component.It can break through the limitation of the traditional Nyquist sampling theorem,which can obtain the recovered signals using less data.Results of simulation experiments prove the validity of the method,as well as the performance ascendency of higher time-delay resolution,data resource utilization and estimation precision by comparing with traditional methods.
出处
《雷达科学与技术》
北大核心
2016年第3期291-296,共6页
Radar Science and Technology
基金
军内科研项目(No.KJ2015XXX)
关键词
压缩感知
线性调频
多径
参数估计
稀疏分解
compressive sensing
linear frequency-modulation（LFM）
multipath
parameter estimation
sparse decomposition
