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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0532-9
DOI :
10.1109/ICASSP.1992.226597
