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    Low complexity algorithms to independently and jointly estimate the location and range of targets using FMCW

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    Type
    Conference Paper
    Authors
    Ahmed, Sajid
    Jardak, Seifallah cc
    Alouini, Mohamed-Slim cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2017-05-12
    Online Publication Date
    2017-05-12
    Print Publication Date
    2016-12
    Permanent link to this record
    http://hdl.handle.net/10754/625013
    
    Metadata
    Show full item record
    Abstract
    The estimation of angular-location and range of a target is a joint optimization problem. In this work, to estimate these parameters, by meticulously evaluating the phase of the received samples, low complexity sequential and joint estimation algorithms are proposed. We use a single-input and multiple-output (SIMO) system and transmit frequency-modulated continuous-wave signal. In the proposed algorithm, it is shown that by ignoring very small value terms in the phase of the received samples, fast-Fourier-transform (FFT) and two-dimensional FFT can be exploited to estimate these parameters. Sequential estimation algorithm uses FFT and requires only one received snapshot to estimate the angular-location. Joint estimation algorithm uses two-dimensional FFT to estimate the angular-location and range of the target. Simulation results show that joint estimation algorithm yields better mean-squared-error (MSE) for the estimation of angular-location and much lower run-time compared to conventional MUltiple SIgnal Classification (MUSIC) algorithm.
    Citation
    Ahmed S, Jardak S, Alouini M-S (2016) Low complexity algorithms to independently and jointly estimate the location and range of targets using FMCW. 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP). Available: http://dx.doi.org/10.1109/GlobalSIP.2016.7906007.
    Sponsors
    This research was funded by a grant from the office of competitive research funding (OCRF) at the King Abdullah University of Science and Technology (KAUST).
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
    Conference/Event name
    2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
    DOI
    10.1109/GlobalSIP.2016.7906007
    Additional Links
    http://ieeexplore.ieee.org/document/7906007/
    ae974a485f413a2113503eed53cd6c53
    10.1109/GlobalSIP.2016.7906007
    Scopus Count
    Collections
    Conference Papers; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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