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
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;
Conference_Titel :
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-3590-2
DOI :
10.1109/CDC.1996.573722
