空天预警研究学报2023，Vol.37Issue(4)：262-267,273,7.DOI:10.3969/j.issn.2097-180X.2023.04.006
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
肖雷 1翁祖鑫 1韩玉兵1
作者信息
- 1. 南京理工大学电子工程与光电技术学院,南京 210094
- 折叠
摘要
Abstract
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 sens-ing 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Key words
space-time-frequency joint sparse/single radio frequency(RF)channel/compressed sensing ar-ray(CSA)/parameter estimation分类
信息技术与安全科学引用本文复制引用
肖雷,翁祖鑫,韩玉兵..基于空时频三维稀疏字典的单通道CSA多参数联合估计[J].空天预警研究学报,2023,37(4):262-267,273,7.
