Threshold Regions in Frequency Estimation

This article addresses the problem of threshold region characterization of the maximum likelihood (ML) sinusoid frequency estimation. We first study on the exact analytical expression of the probability of detection for the ML mean square error for all the signal-to-noise ranges. Then, we propose a...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2022-10, Vol.58 (5), p.4850-4856
Main Authors: Serbes, Ahmet, Qaraqe, Khalid A.
Format: Article
Language:English
Subjects:
Asymptotic properties
Electric breakdown
Frequency estimation
Mathematical models
maximum likelihood
Maximum likelihood detection
Maximum likelihood estimation
Mean square error methods
Probability
probability of detection
Signal to noise ratio
signal-to-noise ratio (SNR) breakdown threshold
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Summary:This article addresses the problem of threshold region characterization of the maximum likelihood (ML) sinusoid frequency estimation. We first study on the exact analytical expression of the probability of detection for the ML mean square error for all the signal-to-noise ranges. Then, we propose a simple asymptotic expression to this ML detection probability and propose a model for the characterization of the variance of the frequency estimation. We also provide asymptotic closed-form expressions to the threshold and the no-information signal-to-noise ratio breakdowns for the ML frequency estimation, respectively. Outcomes of extensive numerical simulations verify our proposed theoretical derivations.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2022.3166063