Comparative Study on Sparse and Recovery Algorithms for Antenna Measurement by Compressed Sensing

被引：0
|
作者：
Zhang, Liang [1 ,2 ]
Wang, Tianting [1 ]
Liu, Yang [1 ]
Kong, Meng [2 ]
Wu, Xianliang [1 ]
机构：
[1] Anhui Univ, Minist Educ Intelligent Comp & Signal Proc, Key Lab, Hefei 230601, Anhui, Peoples R China
[2] Hefei Normal Univ, Anhui Prov Key Lab Simulat & Design Elect Informa, Hefei 230601, Anhui, Peoples R China
来源：
PROGRESS IN ELECTROMAGNETICS RESEARCH M | 2019年 / 81卷
基金：
中国国家自然科学基金;
关键词：
SIGNAL RECOVERY;
D O I：
10.2528/PIERM19041803
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Compressed sensing (CS) is utilized in antenna measurements. The antenna data are compressed using the CS method, and the performances of different sparse and recovery algorithms of CS are used to solve antenna measurements. Experiments are conducted on various types of antennas. The results show that efficiency can be greatly improved by reducing the number of measurement points. The best reconstruction performance is exhibited by the Discrete Wavelet Transform (DWT) algorithm combined with the Compressive Sampling Matching Pursuit (COSAMP) algorithm.
引用
收藏
页码：149 / 158
页数：10
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