Paper Info
Title
Distinguishing ability analysis of compressed sensing radar imaging based on information theory model
Abstract
Recent theory of compressed sensing (CS) has been widely used in many application areas. In this paper, we mainly concentrate on the CS in radar and analyze the distinguishing ability of CS radar image based on information theory model. The information content contained in the CS radar echoes is analyzed by simplifying the information transmission channel as a parallel Gaussian channel, and the relationship among the signal-to-noise ratio (SNR) of the echo signal, the number of required samples, the length of the sparse targets and the distinguishing level of the radar image is gotten. Based on this result, we introduced the distinguishing ability of the CS radar image and some of its properties are also gotten. Real IECAS advanced scanning two-dimensional railway observation (ASTRO) data experiment demonstrates our conclusions.
Year
DOI
Venue
2011
10.1117/12.897595
Proceedings of SPIE
Keywords
Field
DocType
compressed sensing (CS),distinguishing ability,imaging radar,sparse signal reconstruction,information theory model
Radar,Continuous-wave radar,Information theory,Radar engineering details,Computer vision,Radar imaging,Signal-to-noise ratio,Artificial intelligence,Low probability of intercept radar,Geography,Compressed sensing
Conference
Volume
Issue
ISSN
8179
null
0277-786X
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Hai Jiang100.34
bingchen zhang211017.19
yueguan lin3102.04
Wen Hong435549.85
Yirong Wu539646.55