TY - GEN
T1 - Localization of multiple emitters by spatial sparsity methods in the presence of fading channels
AU - Picard, Joseph S.
AU - Weiss, Anthony J.
PY - 2010
Y1 - 2010
N2 - The problem of multiple emitters geolocation using sensor arrays is addressed, in the case of fading channels. A sparsity-based covariance-matrix fitting method is described. The procedure consists of finding a sparse representation of the sample covariance matrices obtained at the arrays, by representing each matrix by an over-complete basis. Sparsity is encouraged by an ℓ1-norm based penalty function. The penalty function is minimized by semi-definite programming. The proposed method provides useful insight and it does not require the identification of the signal and noise subspaces. Therefore, the method does not rely on a good estimate of the number of emitters. Some of the approach properties are super-resolution, robustness to noise, robustness to emitter correlation, no sensitivity to initialization and no need for synchronizing the arrays. Special emphasis is given to uncorrelated sources and uniform linear arrays.
AB - The problem of multiple emitters geolocation using sensor arrays is addressed, in the case of fading channels. A sparsity-based covariance-matrix fitting method is described. The procedure consists of finding a sparse representation of the sample covariance matrices obtained at the arrays, by representing each matrix by an over-complete basis. Sparsity is encouraged by an ℓ1-norm based penalty function. The penalty function is minimized by semi-definite programming. The proposed method provides useful insight and it does not require the identification of the signal and noise subspaces. Therefore, the method does not rely on a good estimate of the number of emitters. Some of the approach properties are super-resolution, robustness to noise, robustness to emitter correlation, no sensitivity to initialization and no need for synchronizing the arrays. Special emphasis is given to uncorrelated sources and uniform linear arrays.
KW - Angle of arrival (AOA)
KW - Convex optimization
KW - Covariance-matrix fitting
KW - Geolocation
KW - Grid-based positioning
KW - Semi-definite programming
KW - Sparsity
KW - Spatial spectrum
KW - Time of arrival (TOA)
KW - ℓ norm
UR - http://www.scopus.com/inward/record.url?scp=78651439259&partnerID=8YFLogxK
U2 - 10.1109/WPNC.2010.5653523
DO - 10.1109/WPNC.2010.5653523
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AN - SCOPUS:78651439259
SN - 9781424471577
T3 - Proceedings of the 2010 7th Workshop on Positioning, Navigation and Communication, WPNC'10
SP - 62
EP - 67
BT - Proceedings of the 2010 7th Workshop on Positioning, Navigation and Communication, WPNC'10
Y2 - 11 March 2010 through 12 March 2010
ER -