• DocumentCode
    2822405
  • Title

    Radar phase-coded waveform design using MOEAs

  • Author

    Stringer, Jeremy ; Lamont, Gary ; Akers, Geoffrey

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Air Force Inst. of Technol., Dayton, OH, USA
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This study applies the NSGA-II, SPEA2, and MOEA/D Multi-Objective Evolutionary Algorithms (MOEAs) to the radar phase coded waveform design problem. The MOEAs are used to generate a series of radar waveform phase codes that have excellent range resolution and Doppler resolution capabilities, while maintaining excellent autocorrelation properties. The study compares the ability of NSGA-II, SPEA2, and MOEA/D to generate a Pareto front of phase code solutions, and then improve upon the quality of the solutions while maintaining a sufficient diversity of available radar phase codes. Results demonstrate that for solving moderate to large instances of the radar phase code problem all three MOEAs generate a diverse set of Pareto optimal radar phase codes. The phase codes generated by NSGA-II have overall better autocorrelation properties than those generated by SPEA2 and MOEA/D, however, all three MOEAs produce useable phase codes.
  • Keywords
    Pareto optimisation; genetic algorithms; phased array radar; radar resolution; Doppler resolution; MOEA/D; NSGA-II; Pareto front; Pareto optimal radar phase codes; SPEA2; autocorrelation property; multiobjective evolutionary algorithm; radar phase-coded waveform; range resolution; Correlation; Doppler effect; Doppler radar; Measurement; Signal to noise ratio; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2012 IEEE Congress on
  • Conference_Location
    Brisbane, QLD
  • Print_ISBN
    978-1-4673-1510-4
  • Electronic_ISBN
    978-1-4673-1508-1
  • Type

    conf

  • DOI
    10.1109/CEC.2012.6256554
  • Filename
    6256554