TY - GEN
T1 - Distributed MIMO radar using compressive sampling
AU - Petropulu, Athina P.
AU - Yu, Yao
AU - Poor, H. Vincent
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - A distributed MIMO radar is considered, in which the transmit and receive antennas belong to nodes of a small scale wireless network. The transmit waveforms could be uncorrelated, or correlated in order to achieve a desirable beampattern. The concept of compressive sampling is employed at the receive nodes in order to perform direction of arrival (DOA) estimation. According to the theory of compressive sampling, a signal that is sparse in some domain can be recovered based on far fewer samples than required by the Nyquist sampling theorem. The DOAs of targets form a sparse vector in the angle space, andtherefore, compressive sampling can be applied for DOA estimation. The proposed approach achieves the superior resolution of MIMO radar with far fewer samples than other approaches. This is particularly useful in a distributed scenario, in which the results at each receive node need to be transmitted to a fusion center.
AB - A distributed MIMO radar is considered, in which the transmit and receive antennas belong to nodes of a small scale wireless network. The transmit waveforms could be uncorrelated, or correlated in order to achieve a desirable beampattern. The concept of compressive sampling is employed at the receive nodes in order to perform direction of arrival (DOA) estimation. According to the theory of compressive sampling, a signal that is sparse in some domain can be recovered based on far fewer samples than required by the Nyquist sampling theorem. The DOAs of targets form a sparse vector in the angle space, andtherefore, compressive sampling can be applied for DOA estimation. The proposed approach achieves the superior resolution of MIMO radar with far fewer samples than other approaches. This is particularly useful in a distributed scenario, in which the results at each receive node need to be transmitted to a fusion center.
KW - Compressive sampling
KW - DOA estimation
KW - MIMO radar
UR - http://www.scopus.com/inward/record.url?scp=70349687422&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349687422&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2008.5074392
DO - 10.1109/ACSSC.2008.5074392
M3 - Conference contribution
AN - SCOPUS:70349687422
SN - 9781424429417
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 203
EP - 207
BT - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
T2 - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Y2 - 26 October 2008 through 29 October 2008
ER -