Threshold Regions in Frequency Estimation

Ahmet Serbes*, Khalid A. Qaraqe

*Corresponding author for this work

Research output: Contribution to journalLetterpeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)4850-4856
Number of pages7
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume58
Issue number5
DOIs
Publication statusPublished - 1 Oct 2022
Externally publishedYes

Keywords

  • Behavior
  • General classes
  • Parameter-estimation
  • Performance lower bounds

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