Title :
An autoregressive moving average tone detector
Author_Institution :
H.R.B.-Singer, State College, PA
Abstract :
A new method for estimating tones in an arbitrary spectrum is presented. An autoregressive-moving average estimator is formulated and transformed into a linear regression problem. Many of the shortcomings of an "all pole" model are overcome and simulated test results indicate that the estimates are not particularly sensitive to additive noise. The main advantages of this new method are computational simplicity and robustness in noise environments. The algorithm can be useful in all areas where spectral information must be extracted in a computationally efficient fashion.
Keywords :
Autoregressive processes; Detectors; Discrete Fourier transforms; Frequency domain analysis; Frequency estimation; Hydrogen; Least squares approximation; Signal processing algorithms; Speech processing; Working environment noise;
Journal_Title :
Proceedings of the IEEE
DOI :
10.1109/PROC.1981.11930