Compressive sensing (CS) is a framework that exploits the compressible character of most natural signals, allowing the accurate measurement of an m-dimensional real signal u in terms of n≪m real measurements v. The CS measurements may be represented in terms of an n × 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 complex media, and therefore in situ CS measurements may be performed simply by exploiting the complex propagation and scattering properties of natural environments. A similar phenomenon is observed in time-reversal imaging, to which connections are made. In addition to presenting the basic in situ CS framework, a simple but practical example problem is considered. © 2007 IEEE.
|Original language||English (US)|
|Title of host publication||2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP|
|Number of pages||4|
|State||Published - Dec 1 2007|