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.
English title
Low complexity subspace approach for unbiased frequency estimation of a complex single-tone
Type
journal article in Web of Science
Language
en
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).
English 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 in English
Frequency estimation; Complex single-tone; Subspace method; Short observation interval
Released
14.11.2023
ISSN
1095-4333
Volume
145
Number
February 2024
Pages from–to
1–20
Pages count
20
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",
year="2023",
volume="145",
number="February 2024",
month="November",
pages="1--20",
issn="1095-4333"
}