基于空时频三维稀疏字典的单通道CSA多参数联合估计  

Multi-parameter joint estimation for single-channel CSA based on space-time-frequency three-dimensional sparse dictionary

作　　者：肖雷 翁祖鑫 韩玉兵[1] XIAO Lei;WENG Zuxin;HAN Yubing(School of Electronic and Optical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学电子工程与光电技术学院,南京210094

出　　处：《空天预警研究学报》2023年第4期262-267,273,共7页JOURNAL OF AIR & SPACE EARLY WARNING RESEARCH

摘　　要：针对单射频通道的压缩感知阵列(compressed sensing array,CSA),提出了一种基于稀疏重构的多参数联合估计方法.首先利用目标在空域和频域上的稀疏特性,以及线性调频(LFM)信号的自相关特性,构建了一种空-时-频三维稀疏字典用于回波信号的稀疏表达;然后基于压缩感知理论对回波信号的投影向量进行稀疏重构,能够直接估计出目标的速度、角度以及距离信息.仿真结果验证了多目标场景下本文所提出的多参数联合估计算法的有效性.This paper proposes a sparse reconstruction based multi-parameter joint estimation method for the compressed sensing array(CSA)with single RF channel.Firstly,the sparse characteristics of the target in space and frequency domain,and the autocorrelation characteristics of linear frequency modulation(LFM)signals are used to construct a space-time-frequency three-dimensional sparse dictionary used for sparse representation of echo signals.Then,the projection vector of the echo signal is reconstructed sparsely based on the compressed sensing theory,enabling the direct estimation of the targets’velocity,angle and range information.Simulation results verify the effectiveness of the proposed multi-parameter joint estimation algorithm in the multi-target scenario.

关 键 词：空-时-频联合稀疏 单射频通道 压缩感知阵列 参数估计 

分 类 号：TN957.51[电子电信—信号与信息处理]