DocumentCode
3242492
Title
Design of signal-subspace cost functionals for parameter estimation
Author
Xu, W. ; Kaveh, M.
Author_Institution
Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA
Volume
5
fYear
1992
fDate
23-26 Mar 1992
Firstpage
405
Abstract
A probabilistic approach to the quantification of the resolving ability of a general class of MUSIC type estimators (m-estimators) is presented. Based on a resolution-maximizing criterion of optimality, a cost functional is designed for a specific parametric subclass of m-estimators. An effective data-adaptive value for the parametric class is also presented and the results are generalized to a broader nonparametric subclass
Keywords
array signal processing; parameter estimation; statistical analysis; MUSIC type estimators; array processing; data-adaptive value; nonparametric subclass; parameter estimation; parametric subclass; probabilistic approach; resolution-maximizing criterion; signal-subspace cost functionals; Azimuth; Cost function; Design optimization; Estimation error; Maximum likelihood estimation; Multiple signal classification; Nonlinear equations; Parameter estimation; Random variables; Signal design;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location
San Francisco, CA
ISSN
1520-6149
Print_ISBN
0-7803-0532-9
Type
conf
DOI
10.1109/ICASSP.1992.226597
Filename
226597
Link To Document