In situ compressive sensing

被引:22
作者
Carin, Lawrence [1 ]
Liu, Dehong [1 ]
Guo, Bin [1 ]
机构
[1] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA
关键词
D O I
10.1088/0266-5611/24/1/015023
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Compressive sensing ( CS) is a framework that exploits the compressible character of most natural signals, allowing the accurate measurement of an m-dimensional signal u in terms of n << m measurements v. The CS measurements may be represented in terms of an n x m matrix that defines the linear relationship between v and u. In this paper, we demonstrate that similar linear mappings of the form u. v are manifested naturally by wave propagation in general media, and therefore in situ CS measurements may be performed simply by exploiting the propagation and scattering properties of natural environments. The connection between the propagation medium and the basis in which u is sparsely rendered is quantified in terms of a mutual-coherence factor, which plays an important role in defining the number of required in situ CS measurements. In addition to presenting the basic in situ CS framework, a simple but practical example problem is considered in detail from multiple perspectives.
引用
收藏
页数:23
相关论文
共 31 条
[1]  
[Anonymous], P PICT COD S PCS BEI
[2]  
[Anonymous], 2001, Probability, Random Variables, and Stochastic Processes
[3]  
[Anonymous], 1993, Ten Lectures of Wavelets
[4]  
[Anonymous], 2006, P COMP IM 4 SPIE EL
[5]  
Balanis C. A., 1989, Advanced engineering electromagnetics
[6]  
Bishop C. M., 2000, P 16 C UNC ART INT S, P46
[7]   Super-resolution in time-reversal acoustics [J].
Blomgren, P ;
Papanicolaou, G ;
Zhao, HK .
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2002, 111 (01) :230-248
[8]  
CANDES E., 2005, ANN STAT
[9]  
CANDES E, 2005, 11 P SPIE C, V5914
[10]   Robust uncertainty principles:: Exact signal reconstruction from highly incomplete frequency information [J].
Candès, EJ ;
Romberg, J ;
Tao, T .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2006, 52 (02) :489-509