Portal de Periódicos da CAPES

Exact maximum likelihood parameter estimation of superimposed exponential signals in noise

1986; Institute of Electrical and Electronics Engineers; Volume: 34; Issue: 5 Linguagem: Inglês

10.1109/tassp.1986.1164949

0096-3518

Yoram Bresler, Albert Macovski,

Structural Health Monitoring Techniques

A unified framework for the exact maximum likelihood estimation of the parameters of superimposed exponential signals in noise, encompassing both the time series and the array problems, is presented. An exact expression for the ML criterion is derived in terms of the linear prediction polynomial of the signal, and an iterative algorithm for the maximization of this criterion is presented. The algorithm is equally applicable in the case of signal coherence in the array problem. Simulation shows the estimator to be capable of providing more accurate frequency estimates than currently existing techniques. The algorithm is similar to those independently derived by Kumaresan et al. In addition to its practical value, the present formulation is used to interpret previous methods such as Prony's, Pisarenko's, and modifications thereof.