Threshold Regions in Frequency Estimation

Serbes A., Qaraqe K.

IEEE Transactions on Aerospace and Electronic Systems, vol.58, no.5, pp.4850-4856, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 58 Issue: 5
  • Publication Date: 2022
  • Doi Number: 10.1109/taes.2022.3166063
  • Journal Name: IEEE Transactions on Aerospace and Electronic Systems
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.4850-4856
  • Keywords: Frequency estimation, maximum likelihood, probability of detection, signal-to-noise ratio (SNR) breakdown threshold
  • Yıldız Technical University Affiliated: Yes


This work 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 closedform expressions to the threshold and the no-information SNR breakdowns for the ML frequency estimation, respectively. Outcomes of extensive numerical simulations verify our proposed theoretical derivations.