Publication detail

Low complexity subspace approach for unbiased frequency estimation of a complex single-tone

POURAFZAL, A. ŠKRABÁNEK, P. CHEFFENA, M. YILDIRIM, S. ROI-TARAVELLA, T.

Original Title

Low complexity subspace approach for unbiased frequency estimation of a complex single-tone

Type

journal article in Web of Science

Language

English

Original Abstract

We propose a single-tone frequency estimator of a one-dimensional complex signal in complex white Gaussian noise. The estimator is based on the subspace approach and the unitary transformation. Due to its low space and time-complexity, we name the estimator as Low complexity Unitary Principal-singular-vector Utilization for Model Analysis (LUPUMA). Regardless of the observation length, LUPUMA provides a uniform estimation variance over the whole frequency range, while achieving the lowest time-complexity among subspace methods. The proposed estimator asymptotically reaches the Cramér-Rao Lower Bound. For short observations, the signal-to-noise ratio threshold of LUPUMA corresponds to the threshold of the maximum likelihood estimator. The low space and time-complexity along with the stable and state-of-the-art estimation performance for short observations make LUPUMA an ideal candidate for applications with a limited number of signal samples, limited computational power, limited memory, and for applications that require rapid processing time (low latency).

Keywords

Frequency estimation; Complex single-tone; Subspace method; Short observation interval

Authors

POURAFZAL, A.; ŠKRABÁNEK, P.; CHEFFENA, M.; YILDIRIM, S.; ROI-TARAVELLA, T.

Released

14. 11. 2023

ISBN

1095-4333

Periodical

Digital Signal Processing: A Review Journal

Year of study

145

Number

February 2024

State

United States of America

Pages from

1

Pages to

20

Pages count

20

URL

https://www.sciencedirect.com/science/article/pii/S1051200423003998

BibTex

@article{BUT185653,
  author="Alireza {Pourafzal} and Pavel {Škrabánek} and Michael {Cheffena} and Sule {Yildirim} and Thomas {Roi-Taravella}",
  title="Low complexity subspace approach for unbiased frequency estimation of a complex single-tone",
  journal="Digital Signal Processing: A Review Journal",
  year="2023",
  volume="145",
  number="February 2024",
  pages="1--20",
  doi="10.1016/j.dsp.2023.104304",
  issn="1095-4333",
  url="https://www.sciencedirect.com/science/article/pii/S1051200423003998"
}