DocumentCode
3407422
Title
High resolution radar imaging based on compressed sensing and adaptive Lp norm algorithm
Author
Min, Wang
Author_Institution
Nat. Key Lab. of Radar Signal Process., Xidian Univ., Xi´´an, China
Volume
1
fYear
2011
fDate
24-27 Oct. 2011
Firstpage
206
Lastpage
209
Abstract
Radar imaging based compressive sensing (CS) is a potential way to obtain the high-resolution radar images without the constraint of Nyquist sampling rate. In this paper, we proposed a radar remote-sensing imaging approach based on compressive sensing and adaptive Lp norm algorithm. Some experiments are taken and the results indicate that an accurate reconstruction of high-resolution radar images are obtained, with fewer measurements than its counterparts, but resulting in lower normalized MSE(NMSE).
Keywords
compressed sensing; image reconstruction; image sampling; radar imaging; remote sensing by radar; Nyquist sampling; adaptive Lp norm algorithm; compressed sensing; high resolution radar imaging; image reconstruction; normalized MSE; radar remote sensing imaging; Compressed sensing; Image reconstruction; Imaging; Optimization; Radar imaging; Radar remote sensing; Adaptive Lp Norm Algorithm; Compressive sensing; Radar imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Radar (Radar), 2011 IEEE CIE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-8444-7
Type
conf
DOI
10.1109/CIE-Radar.2011.6159512
Filename
6159512
Link To Document