Title :
Direction finding networks based on the approximate maximum likelihood and covariance fit formulations
Author :
Goryn, D. ; Kaveh, M.
Author_Institution :
Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA
Abstract :
Competitive feedback network solutions for narrowband direction finding are developed. The main interest lies in estimating the directions of arrival for closely spaced sources. It is shown that if there is a priori information about the number of sources a conditional maximum likelihood solution can be obtained by the network. A suboptimal estimator that requires no a priori knowledge about the number of signals and a network that performs a covariance fit is also presented. Results are presented using both synthetic and real array data
Keywords :
feedback; radio direction-finding; signal detection; DOA estimation; approximate maximum likelihood; closely spaced sources; conditional maximum likelihood solution; covariance fit formulations; direction finding networks; directions of arrival; feedback network solutions; narrowband direction finding; real array data; synthetic array data; Array signal processing; Computer networks; Direction of arrival estimation; Lyapunov method; Maximum likelihood estimation; Narrowband; Neural networks; Phased arrays; Sensor arrays; Signal resolution;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-0003-3
DOI :
10.1109/ICASSP.1991.150097