• DocumentCode
    1482651
  • Title

    Pareto-optimal radar waveform design

  • Author

    De Maio, A. ; Piezzo, M. ; Farina, A. ; Wicks, Mike

  • Author_Institution
    Dipt. di Ing. Biomed. Elettron. e delle Telecomun., Univ. degli Studi di Napoli Federico II, Naples, Italy
  • Volume
    5
  • Issue
    4
  • fYear
    2011
  • fDate
    4/1/2011 12:00:00 AM
  • Firstpage
    473
  • Lastpage
    482
  • Abstract
    This study deals with the problem of Pareto-optimal waveform design in the presence of coloured Gaussian noise, under a similarity and an energy constraint. At the design stage, the authors, determine the optimal radar code according the following criterion: constrained maximisation of the detection performance and constrained minimisation of the Cramer-Rao lower bound (CRLB) on the Doppler estimation accuracy. This is tantamount to jointly maximising two quadratic forms under two quadratic constraints, so that the problem can be formulated in terms of a non-convex multi-objective optimisation problem. In order to solve it, the authors resort to the scalarisation technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions. At the analysis stage, the authors assess the performance of the proposed waveform design scheme in terms of detection performance, region of achievable Doppler estimation accuracy and ambiguity function. In particular, the authors analyse the role of the Pareto weight in the optimisation process.
  • Keywords
    Gaussian noise; concave programming; radar signal processing; CRLB; Cramer-Rao lower bound; Doppler estimation accuracy; Pareto-optimal radar waveform design; ambiguity function; coloured Gaussian noise; nonconvex multi-objective optimisation problem; quadratic constraint; scalarisation technique;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar & Navigation, IET
  • Publisher
    iet
  • ISSN
    1751-8784
  • Type

    jour

  • DOI
    10.1049/iet-rsn.2010.0184
  • Filename
    5739669