@article {12467,
	title = {COMPRESSIVE SENSING SYSTEM AND METHOD FOR BEARING ESTIMATION OF SPARSE SOURCES IN THE ANGLE DOMAIN},
	volume = {12/740,947},
	year = {2010},
	month = {2010/10/21/},
	abstract = {Compressive Sensing (CS) is an emerging area which uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or com-pressible signals. Direction-of-arrival (DOA) estimation is performed with an array of sensors using CS. Using random projections of the sensor data, along with a full waveform recording on one reference sensor, a sparse angle space scenario can be reconstructed, giving the number of sources and their DOA{\textquoteright}s. Signal processing algorithms are also developed and described herein for randomly deployable wireless sensor arrays that are severely constrained in communication bandwidth. There is a focus on the acoustic bearing estimation problem and it is shown that when the target bearings are modeled as a sparse vector in the angle space, functions of the low dimensional random projections of the microphone signals can be used to determine multiple source bearings as a solution of an 1]-norm minimization problem.},
	url = {http://www.google.com/patents?id=xDLYAAAAEBAJ},
	author = {Cevher,Volkan and Gurbuz,Ali Cafer and McClellan,James H. and Chellapa, Rama}
}
