A highly accurate DFT-based parameter estimator for complex exponentials
DOI:
https://doi.org/10.26636/jtit.2006.1.354Keywords:
frequency estimation, phase estimation, amplitude estimation, DFT-based parameter estimation, spectral estimation, digital signal processing algorithm, complex exponential parameter estimationAbstract
A highly accurate DFT-based complex exponential parameter estimation algorithm is presented in this paper. It will be shown that for large number of samples and high signal to noise ratio (SNR), the phase estimation error variance performance is only 0.0475 dB above the Cramer-Rao lower bound (CRLB) for phase estimation with unknown frequency and phase. The amplitude estimation error variance performance was found to lay on the CRLB for amplitude estimation. Exact phase and amplitude estimation can be achieved in the noiseless case with this algorithm. The algorithm has low implementation computational complexity and is suitable for numerous real time digital signal processing applications.
Downloads
References
[1] S. Reisenfeld, "A highly accurate algorithm for the estimation of the frequency of a complex exponential in additive Gaussian noise", in 5th Austr. Commun. Theory Worksh., Newcastle, Australia, 2004, pp. 154-158.
View in Google Scholar
[2] S. Reisenfeld and E. Aboutanios, "A new algorithm for the estimation of the frequency of a complex exponential in additive Gaussian noise", IEEE Commun. Lett., vol. 7, issue 11, pp. 549-551, 2003.
View in Google Scholar
[3] D. C. Rife and R. Boorstyn, "Single tone parameter estimation from discrete-time observations", IEEE Trans. Inform. Theory, vol. IT-20, no. 5, pp. 591-598, 1974.
View in Google Scholar
[4] S. Kay, "A fast and accurate signal frequency estimator", IEEE Trans. Acoust., Speech Sig. Proces., vol. 37, no. 12, pp. 1987-1990, 1989.
View in Google Scholar
[5] R. Schmidt, "Multiple emitter location and signal parameter estimation", IEEE Trans. Anten. Propagat., vol. 34, no. 3, pp. 276-280, 1986.
View in Google Scholar
[6] R. Roy and T. Kailath, "ESPRIT - estimation of signal parameters via rotational invariance techniques", IEEE Trans. Acoust., Speech Sig. Proces., vol. 37, no. 7, pp. 984-995, 1989.
View in Google Scholar
[7] S. M. Kay, Fundamentals of Statistical Signal Processing Estimation Theory. Upper Saddle River: Prentice Hall, 1993.
View in Google Scholar
[8] Problems in Probability Theory, Mathematical Statistics and Theory of Random Functions, A. A. Sveshnikov, Ed. New York: Dover, 1968.
View in Google Scholar
[9] B. James, B. D. O. Anderson, and R. C. Williamson, "Characterization of threshold for single tone maximum likelihood frequency estimation", IEEE Trans. Sig. Proces., vol. 43, pp. 817-821, 1995.
View in Google Scholar
[10] A. O. Steinhardt and C. Bretherton, "Thresholds in frequency estimation", in Proc. ICASSP, Tampa, USA, 1985, vol. 10, pp. 1273-1276.
View in Google Scholar
[11] B. G. Quinn and P. J. Kootsookos, "Threshold behavior of the maximum likelihood estimator of frequency", IEEE Trans. Sig. Proces., vol. 42, pp. 3291-3294, 1994.
View in Google Scholar
[12] L. Knockaert, "The Barankin bound and threshold behavior in frequency estimation", IEEE Trans. Sig. Proces., vol. 45, pp. 2398-2401, 1997.
View in Google Scholar
[13] D. G. Manolakis, V. K. Ingle, and S. M. Kogon, Statistical and Adaptive Signal Processing - Spectral Estimation, Signal Modelling, Adaptive Filtering and Array Processing. Boston: McGraw Hill, 2000.
View in Google Scholar
Downloads
Submitted
Published
Issue
Section
License
Copyright (c) 2006 Journal of Telecommunications and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
