TY - JOUR
T1 - On the deterministic CRB for DOA estimation in unknown noise fields using sparse sensor arrays
AU - Kleinsteuber, Martin
AU - Seghouane, Abd Krim
PY - 2008/2
Y1 - 2008/2
N2 - The Cramé-Rao bound (CRB) plays an important role in direction of arrival (DOA) estimation because it is always used as a benchmark for comparison of the different proposed estimation algorithms. In this correspondence, using well-known techniques of global analysis and differential geometry, four necessary conditions for the maximum of the log-likelihood function are derived, two of which seem to be new. The CRB is derived for the general class of sensor arrays composed of multiple arbitrary widely separated subarrays in a concise way via a coordinate free form of the Fisher Information. The result derived in [1] is confirmed.
AB - The Cramé-Rao bound (CRB) plays an important role in direction of arrival (DOA) estimation because it is always used as a benchmark for comparison of the different proposed estimation algorithms. In this correspondence, using well-known techniques of global analysis and differential geometry, four necessary conditions for the maximum of the log-likelihood function are derived, two of which seem to be new. The CRB is derived for the general class of sensor arrays composed of multiple arbitrary widely separated subarrays in a concise way via a coordinate free form of the Fisher Information. The result derived in [1] is confirmed.
KW - Cramér-Rao bound (CRB)
KW - Differential geometry
KW - Direction of arrival (DOA) estimation
KW - Maximum likelihood
UR - http://www.scopus.com/inward/record.url?scp=39649107334&partnerID=8YFLogxK
U2 - 10.1109/TSP.2007.907832
DO - 10.1109/TSP.2007.907832
M3 - Article
SN - 1053-587X
VL - 56
SP - 860
EP - 864
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 2
ER -