TY - GEN
T1 - The hybrid Cramer-Rao lower bound - from practice to theory
AU - Messer, Hagit
PY - 2006
Y1 - 2006
N2 - In 1987, Rockah and Schultheiss [1] introduced the Hybrid Cramer-Rao Lower Bound (HCRLB) as an extension of the classical Cramer-Rao bound (CRLB). Whereas the classical CRLB is applicable to the estimation of non-random parameters, and the Bayesian CRLB applies to random parameters, the HCRLB is applicable to the joint estimation of random and non-random parameters. In this paper wes review the basic theory of the multi-parameter Cramer-Rao type bounds in a unified framework. Then, we discus the limitations of the HCRLB which may explain why it has not been introduced till needed for a certain array processing application, where it has shown to be useful.
AB - In 1987, Rockah and Schultheiss [1] introduced the Hybrid Cramer-Rao Lower Bound (HCRLB) as an extension of the classical Cramer-Rao bound (CRLB). Whereas the classical CRLB is applicable to the estimation of non-random parameters, and the Bayesian CRLB applies to random parameters, the HCRLB is applicable to the joint estimation of random and non-random parameters. In this paper wes review the basic theory of the multi-parameter Cramer-Rao type bounds in a unified framework. Then, we discus the limitations of the HCRLB which may explain why it has not been introduced till needed for a certain array processing application, where it has shown to be useful.
UR - http://www.scopus.com/inward/record.url?scp=34250771748&partnerID=8YFLogxK
U2 - 10.1109/SAM.2006.1677208
DO - 10.1109/SAM.2006.1677208
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AN - SCOPUS:34250771748
SN - 1424403081
SN - 9781424403080
T3 - 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
SP - 304
EP - 307
BT - 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
T2 - 4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
Y2 - 12 July 2006 through 14 July 2006
ER -