A unified framework for the exact maximum likelihood estimation of the parameters of superimposed exponential signals in noise, encompassing both the single- and multiexperiment cases (respectively, the time series and the array problems), is presented. An exact expression for the ML criterion is derived in terms of the prediction polynomial of the noiseless signal, and an iterative algorithm for the maximization of this criterion is presented. A simulation example shows the estimator to be capable of providing more accurate frequency estimates than existing techniques.
|Number of pages
|ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
|Published - 1985
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering