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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F23%3APU149779" target="_blank" >RIV/00216305:26210/23:PU149779 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S1051200423003998" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1051200423003998</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.dsp.2023.104304" target="_blank" >10.1016/j.dsp.2023.104304</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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).

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Digital Signal Processing: A Review Journal

  • ISSN

    1051-2004

  • e-ISSN

    1095-4333

  • Volume of the periodical

    145

  • Issue of the periodical within the volume

    February 2024

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    20

  • Pages from-to

    1-20

  • UT code for WoS article

    001165305400001

  • EID of the result in the Scopus database

    2-s2.0-85178663373