Title :
A novel cyclic algorithm for maximum likelihood frequency estimation
Author :
Shaw, Amab Kumar
Author_Institution :
Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
Abstract :
An algorithm for estimation of frequencies of narrowband sources from noisy observation data is presented. For Gaussianly distributed noise, the algorithm produces maximum likelihood estimates, otherwise least-squares estimates, are obtained. The proposed algorithm is iterative, and at each step of iteration the optimization is with respect to a single frequency only, and hence simple hardware/software is sufficient for implementation. The performance of the algorithm has been compared with theoretical Cramer-Rao bounds.<>
Keywords :
iterative methods; least squares approximations; optimisation; parameter estimation; signal processing; Cramer-Rao bounds; Gaussianly distributed noise; cyclic algorithm; iterative methods; least squares approximations; least-squares estimates; maximum likelihood frequency estimation; narrowband sources; noisy observation data; optimization; parameter estimation; signal processing; Iterative methods; Least squares methods; Optimization methods; Parameter estimation; Signal processing;
Conference_Titel :
Systems Engineering, 1991., IEEE International Conference on
Conference_Location :
Dayton, OH, USA
Print_ISBN :
0-7803-0173-0
DOI :
10.1109/ICSYSE.1991.161165
