DocumentCode
307097
Title
Maximum likelihood parameter estimation of a sinusoid with random amplitude in white noise
Author
Sakai, Hideaki ; Hayashi, Toshiyuki
Author_Institution
Div. of Appl. Syst. Sci., Kyoto Univ., Japan
Volume
3
fYear
1996
fDate
11-13 Dec 1996
Firstpage
3545
Abstract
This paper deals with the maximum likelihood (ML) estimation of parameters of a sinusoid with random amplitude modeled by an autoregressive process in white noise. Using the EM algorithm, an efficient ML estimate is constructed. Some simulation results are presented to see that the performance of the estimate is close to that predicted by the corresponding Cramer-Rao bound
Keywords
autoregressive processes; maximum likelihood estimation; signal processing; white noise; Cramer-Rao bound; EM algorithm; autoregressive process; maximum likelihood estimation; parameter estimation; random amplitude; sinusoid; white noise; Autoregressive processes; Doppler radar; Frequency estimation; Iterative algorithms; Maximum likelihood estimation; Parameter estimation; Predictive models; Radar signal processing; Signal processing algorithms; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location
Kobe
ISSN
0191-2216
Print_ISBN
0-7803-3590-2
Type
conf
DOI
10.1109/CDC.1996.573722
Filename
573722
Link To Document